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Renowned for its organic richness, unconventional shale presents both unique challenges and opportunities for hydrocarbon extraction and various geo-engineering applications, owing to its complex storage, flow, and stimulation properties. It is essential, from a multidisciplinary perspective, to characterize the rock physics response and construct rock physics model for unconventional shale reservoirs. A maturity-constrained rock physics modeling method for shales, in conjunction with geochemical analyses, is proposed, employing the stepwise homogenization method to quantify the scale-dependent elastic and anisotropic behavior of laminated shales. Considering the complex pore structure of shale, combined with the microscale effects of fluid transport, various forces, and microfracture features, the multiphase fluid flow behavior can be accurately characterized. Then, from the perspective of fracturing performance, it is necessary to develop a new fracability evaluation model for unconventional shale reservoirs. This model integrates fracture mechanics theory, the elastic and mechanical properties of rocks, fracturing operations, reservoir geological characteristics, and in-situ stress to thoroughly evaluate fracability. Unconventional petrophysicists must move beyond traditional hydrocarbon evaluation to embrace interdisciplinary approaches, which requires comprehensive understanding and characterization of the storage, flow, and stimulation capacities, thereby optimizing development strategies and maximize resource utilization. [ABSTRACT FROM AUTHOR]

Accurate characterization for effective elastic moduli of porous solids is crucial for better understanding their mechanical behaviour and wave propagation, which has found many applications in the fields of engineering, rock physics and exploration geophysics. We choose the spheroids with different aspect ratios to describe the various pore geometries in porous solids. The approximate equations for compressibility and shear compliance of spheroid pores and differential effective medium theory constrained by critical porosity are used to derive the asymptotic solutions for effective elastic moduli of the solids containing randomly oriented spheroids. The critical porosity in the new asymptotic solutions can be flexibly adjusted according to the elastic moduli – porosity relation of a real solid, thus extending the application of classic David‐Zimmerman model because it simply assumes the critical porosity is one. The asymptotic solutions are valid for the solids containing crack‐like oblate spheroids with aspect ratio α$\alpha $< 0.3, nearly spherical pores (0.7 < α$\alpha $< 1.3) and needle‐like prolate pores with α$\alpha $ > 3, instead of just valid in the limiting cases, for example perfectly spherical pores (α$\alpha $= 1) and infinite thin cracks (α→$\alpha \ \to $0). The modelling results also show that the accuracies of asymptotic solutions are weakly affected by the critical porosity ϕc${{\phi }_{\mathrm{c}}}$ and grain Poisson's ratio v0${{v}_0}$, although the elastic moduli have appreciable dependency of ϕc${{\phi }_{\mathrm{c}}}$ and v0${{v}_0}$. We then use the approximate equations for pore compressibility and shear compliance as inputs into the Mori–Tanaka and Kuster–Toksoz theories and compare their calculations to our results from differential effective medium theory. By comparing the published laboratory measurements with modelled results, we validate our asymptotic solutions for effective elastic moduli. [ABSTRACT FROM AUTHOR]

We present novel experimental measurements of acoustic velocity and attenuation in unconsolidated sand with water saturation within the sonic (well‐log analogue) frequency range of 1–20 kHz. The measurements were conducted on jacketed sand packs with 0.5‐m length and 0.069‐m diameter using a bespoke acoustic pulse tube (a water‐filled, stainless steel, thick‐walled tube) under 10 MPa of hydrostatic confining pressure and 0.1 MPa of atmospheric pore pressure. We assess the fluid distribution effect on our measurements through an effective medium rock physics model, using uniform and patchy saturation approaches. Our velocity and attenuation (Q−1) are accurate to ±2.4% and ±5.8%, respectively, based on comparisons with a theoretical transmission coefficient model. Velocity decreases with increasing water saturation up to ∼75% and then increases up to the maximum saturation. The velocity profiles across all four samples show similar values with small differences observed around 70%–90% water saturation, then converging again at maximum saturation. In contrast, the attenuation increases at low saturation, followed by a slight decrease towards maximum saturation. Velocity increases with frequency across all samples, which contrasts with the complex frequency‐dependent pattern of attenuation. These results provide valuable insights into understanding elastic wave measurements over a broad frequency spectrum, particularly in the sonic range. [ABSTRACT FROM AUTHOR]

Crystalline rocks in the subsurface are of interest for geothermal energy extraction, nuclear waste storage, and, when weathered or fractured, as aquifers. Compliant discontinuities such as microcracks, cracks and fractures may nucleate and propagate due to changes in pore pressure, stress and temperature. These discontinuities may provide flow pathways for fluids and, if fracturing extends to surrounding rocks, may allow escape of fluids to neighbouring formations. Monitoring such rocks using sonic logs, passive seismic, borehole seismic and surface seismic requires understanding of the propagation of elastic waves in the presence of such discontinuities. These may have an anisotropic orientation distribution as in situ stress may be anisotropic. As crystalline rock may display intrinsic anisotropy due to foliation and the preferential orientation of anisotropic minerals, quantification of the relative importance of intrinsic and microcrack‐induced anisotropy is important. This may be achieved based on the stress sensitivity of elastic wave velocities. A method that allows both the orientation distribution of microcracks and the stress dependence of their normal and shear compliance to be estimated independently of the elastic anisotropy of the background rock is presented. Results are given for anisotropic samples of gneiss from Bukov in the Czech Republic and granite from Grimsel in Switzerland based on the ultrasonic velocity measurements of Aminzadeh et al. The microcrack orientation distribution is approximately transversely isotropic for both samples with a preferred orientation of microcrack normals perpendicular to foliation. This preferred alignment is stronger in the sample of gneiss than in the granite sample, and the normal and shear compliance of the microcracks decreases with increasing compressive stress. This occurs because the contact between opposing faces of the discontinuities grows with increasing compressive stress, and this results in a decrease in elastic anisotropy with increasing compressive stress. At low stress, the ratio of microcrack normal compliance to shear compliance is approximately 0.25 for the granite sample and 0.7 for the sample of gneiss. The normal compliance ZN for both samples decreases faster with increasing compressive stress than the shear compliance ZT, resulting in a decrease in ZN/ZT with increasing compressive stress. [ABSTRACT FROM AUTHOR]

Fracture interactions are an important factor that affects rock effective elastic properties. We study the fracture interaction effects by combinations of theoretical modelling, numerical simulations and experiments in this work. First, we propose a simplified differential effective medium scheme and self‐consistent approximation for effective elastic properties of rocks with aligned fractures, and we compare their results to those of non‐interaction approximation. The results show that the predictions by differential effective medium scheme and self‐consistent approximation are lower than those by non‐interaction approximation. This indicates that the differential effective medium scheme and self‐consistent approximation quantify the stress amplification effects but not stress shielding effects. To validate this, we carry out numerical simulations for cases with coplanar cracks and stacked cracks, respectively. We find that the stress shielding effect (stacked cracks) causes a significant increment of effective elastic stiffnesses of fractured rocks. However, the stress amplification (coplanar cracks) has the opposite effect, which induces a slight reduction in rock effective elastic stiffnesses. The differential effective medium scheme quantifies the lower bound for this effect well. Besides numerical simulations, applying theoretical models in experimental measurements also shows a pronounced effect of stress shielding but a small influence of stress amplification on fractured rock elastic properties. This work indicates that the stress shielding is an important effect that affects fractured rock elastic properties. Without considering this effect, the fracture density may be largely underestimated by the seismic or sonic logging inversion. Hence, the models accounting for stress shielding effects need to be developed in the future, which can combine with the above models for the seismic or sonic logging inversion of fracture properties. [ABSTRACT FROM AUTHOR]

Reservoir transformation is essential for developing gas hydrate reservoirs. Predicting sediment brittleness is key to optimizing drilling design and evaluating engineering sweet spots. Constructing a brittleness index reflecting the brittle mineral content of a rock based on elastic parameters and predicting it using seismic data is a feasible solution for assessing reservoir brittleness. In addition, the elastic brittleness index can characterize the effect of complex pore types, fractures and pore fillings on rock brittleness. With the shallow hydrate reservoir in the sea as the research target. First, a novel brittleness index characterized by multiplying the Lamé parameter (λ$\lambda $) by Poisson's ratio (σ$\sigma $) is proposed. Its superiority in indicating brittle mineral content is verified by a rock‐physics model. Second, a reflection coefficient approximation equation including the novel brittleness index is derived, enabling direct estimation of reservoir brittleness from seismic data. The new brittleness index has proven to better reflect brittle mineral content and effectively indicate the high brittleness characteristics of hydrate reservoirs. The accuracy of the proposed approximate equation is verified by a layered medium model, and the viability of predicting the new brittleness index using seismic data is also theoretically supported by the model test. Finally, the proposed method has obtained favourable results in the application of hydrate work area data collected at the South China Sea, confirming its availability and practicality. [ABSTRACT FROM AUTHOR]

A new method for estimating petrophysical properties from elastic well log or seismic data is evaluated on data from the Carnarvon Basin, Northwest Australia. The study has utilized well and seismic inversion data covering part of the Triassic‐aged fluvio‐deltaic Mungaroo Formation on the Exmouth Plateau. The method applied is based on several recently published papers to use acoustic impedance, velocity ratio Vp/Vs and estimated constants to calculate clay volume (VCL), effective porosity and water saturation (SW). The case study showed exceptional results on well data. A strong match is observed between petrophysically derived VCL, effective porosity and SW and the estimates derived from elastic logs. When applied to seismic inversion volumes, pay in the wells is predicted from seismic, and porosity of the sands can be estimated with confidence. Petrophysical properties for nearby direct hydrocarbon indicator–supported prospects could also be evaluated, although an imprint of the direct hydrocarbon indicator was observed on the VCL prediction, and overall predictions are less than expected based on regional well results. Using these results, a minor modification is proposed to the equations used, and a workflow is derived to enable easy application to other projects. The modified approach was validated on the well data from the original publication. The results also indicate that the approach can be used to help identify erroneous synthetic Vs estimates in limited data settings. [ABSTRACT FROM AUTHOR]

Shear slowness data are crucial data in rock physics analysis and seismic reservoir characterization. In petrophysical formation evaluation, the use of sonic data is limited, and hence, sonic data, especially shear sonic, are not considered as critical. In many deep-water wells to save the cost of operations, shear sonic data are not recorded. In these scenarios for rock physics analysis, it becomes necessary to predict shear sonic data from other available datasets. Conventional techniques for shear slowness predictions rely on empirical relations and rock physics modeling. However, these approaches require extensive information as input and additionally carry assumptions and multiple prerequisites. Presently with the advancement of computing power Machine learning (ML) emerges as a robust and optimized technique for predicting precise DTS in quick time and with fewer input datasets. In this study, wells located in the deep-waters of the East Coast of India and penetrated siliciclastic reservoirs of both compacted sand and soft high porosity sands were used as input to train the ML algorithm. Random Forest machine learning algorithm is best used for both classification and regression tasks, and this algorithm is used here for the data prediction. As a comparison, the convolutional LSTM method is also used for data prediction. To comply with the geological variability in the prediction and to enhance the prediction accuracy, rock physics understandings were used as a guide in feature engineering. The RF prediction shows a good match of ~ 93%, and the LSTM model prediction shows ~ 94% correlation at validation well. Both the model predicted data show good agreement with the rock physics modeling interpretations at the target well. [ABSTRACT FROM AUTHOR]

Geophysical monitoring of CO2 geological sequestration represents a critical technology for ensuring the long-term safe storage of CO2 while verifying its characteristics and dynamic changes. Currently, the primary geophysical monitoring methods employed in CO2 geological sequestration include seismic, fiber optic, and logging technologies. Among these methods, seismic monitoring techniques encompass high-resolution P-Cable three-dimensional seismic systems, delayed vertical seismic profiling technology, and four-dimensional distributed acoustic sensing (DAS). These methods are utilized to monitor interlayer strain induced by CO2 injection, thereby indirectly determining the injection volume, distribution range, and potential diffusion pathways of the CO2 plume. In contrast, fiber optic monitoring primarily involves distributed fiber optic sensing (DFOS), which can be further classified into distributed acoustic sensing (DAS) and distributed temperature sensing (DTS). This technology serves to complement seismic monitoring in observing interlayer strain resulting from CO2 injection. The logging techniques utilized for monitoring CO2 geological sequestration include neutron logging methods, such as thermal neutron imaging and pulsed neutron gamma-ray spectroscopy, which are primarily employed to assess the sequestration volume and state of CO2 plumes within a reservoir. Seismic monitoring technology provides a broader monitoring scale (ranging from dozens of meters to kilometers), while logging techniques operate at centimeter to meter scales; however, their results can be significantly affected by the heterogeneity of a reservoir. [ABSTRACT FROM AUTHOR]

The elastic properties and wave propagation of porous rocks are sensitive to the stress variation. The existing theories mainly focus on the impacts of effective stress, confining and pore pressures. The physics of uniaxial stress effect on rock elasticity and wave propagation is seldom well studied, although the uniaxial stress case is frequently encountered in several scenarios, such as the laboratory loading and the subsurface tectonic deformation. Therefore, we propose a new dual‐porosity model to describe the effect of uniaxial effective stress on elastic properties of dry porous rocks, based on the Palmer equation and Shapiro dual‐porosity model. The Gurevich squirt‐flow model is then incorporated to model the dispersion and attenuation of wave velocities of fluid‐saturated porous rocks. Modelling results show that the increase of uniaxial effective stress inflates the P‐ and S‐wave velocities along the stress direction until the velocities asymptotically reach their maximum values within the elastic limit. However, the relevant wave dispersion and attenuation gradually decline with the elevating stress possibly due to the gradual closure of cracks. The effect of viscosity, fluid modulus and crack aspect ratio on wave dispersion is investigated in detail as well. By comparing our model to the published laboratory ultrasonic measurements, we confirm the validity of our model. Furthermore, our dual‐porosity model is used to establish a rock‐physics approach to estimate the wave velocities with the well‐logging data. The well‐logging examples show the reasonable agreement between the predicted results and real data, illustrating the feasibility of our approach. [ABSTRACT FROM AUTHOR]

The mechanical behavior of composite granular rocks is a multifaceted phenomenon with broad relevance in various geomechanical applications. Traditional homogenization models and continuum mechanics-based numerical methods often fall short of accurately capturing the intricacies of granular materials. Granular materials exhibit heterogeneity and arching mechanisms governing the force networks that ensure system stability. Unlike continuum-based approaches, discrete element methods (DEM) have an advantage in assessing effective material properties by considering material heterogeneity and grain-level physical interactions. This study evaluates effective elastic properties using DEM with flat-joint contact law for composite binary mixtures with a stiff inclusion embedded within a matrix material. We examine variations in the elastic properties across different structural and laminated geometrical distributions of inclusion materials. Our findings closely adhere to the Voigt-Reuss and Hashin–Strikman bounds within their specific conditions, demonstrating the promising application of DEM in the analysis of composite materials. In addition, our research provides an in-depth analysis of the distinctive stress-evolution and damage-evolution characteristics exhibited by various geometrical configurations of inclusions under unconfined compressive loading. These results offer invaluable insights into the mechanical behavior of composite granular rocks and underscore the potential applications of DEM in addressing rock physics modeling problems encountered in petroleum engineering. Highlights: The study's findings validate the use of discrete element modeling in predicting the effective mechanical behavior of composite rocks. Effective elastic properties of composite rocks estimated using the discrete element method are well constrained by Hashin–Shtrikman and Voigt–Reuss bounds. The research uncovers different behaviors in elastic moduli for isotropic and laminated inclusion scenarios. Stress and strain exhibit distinct patterns of evolution within materials possessing different properties. The study highlights distinct material behaviors under different loading conditions and composite compositions, shedding light on how composition, geometry, and loading direction influence crack formation and sample failure. [ABSTRACT FROM AUTHOR]

We adopt extreme value theory to estimate the upper limit of the next record‐breaking magnitudes of induced seismic events. The methodology is based on order statistics and does not rely on knowledge of the state of the subsurface reservoir or injection strategy. The estimation depends on the history of record‐breaking events produced by the anthropogenic activities. We apply the methodology to three different types of industrial operations: natural gas production, saltwater disposal and hydraulic fracturing. We show that the upper limit estimate provides a reliable and realistic upper bound for magnitudes of the record‐breaking events in investigated datasets including 15 publicly available datasets. The predicted magnitudes do not overestimate the observed magnitudes by more than 1.0 magnitude unit and underestimation is rare, probably resulting from insufficient sampling of the statistical distribution of the induced seismicity. The richest dataset, sourced from downhole and surface monitoring of the Preston New Road hydraulic fracturing, provides reliable estimates of the magnitudes over three orders of magnitudes with only slight underprediction of the largest observed event. While the detection of weaker events improves the performance of the method, we show that it can be applied even with a few observed record‐breaking events to provide reliable estimates of magnitudes. However, care must be taken to ensure that event catalogues are estimated consistently across a range of magnitudes. [ABSTRACT FROM AUTHOR]

The interlayer wave‐induced fluid flow is an important mechanism for seismic attenuation and dispersion, as well as frequency‐dependent anisotropy, in the fluid‐saturated porous layered medium. This mechanism is closely related to the medium physical properties, and thus quantifying this mechanism is of significance for the seismic inversion of medium physical properties. Although numerous models have been proposed to quantify this mechanism, most models do not consider the effects of layer intrinsic anisotropy. To solve this problem, the effective complex‐valued and frequency‐dependent stiffness coefficients are derived for the fluid‐saturated porous medium composed of periodic transversely isotropic layers. Using the derived solutions, we study the effects of layer intrinsic anisotropy on seismic dispersion and attenuation, as well as frequency‐dependent anisotropy. It has been found that different matrix or fluid property contrasts between adjacent layers lead to different effects of intrinsic anisotropy. In addition, the effects of intrinsic anisotropy are also influenced by the fluid distribution when both matrix and fluid properties contrast among adjacent layers exist. In the low‐ and high‐frequency limits of wave‐induced fluid flow, our model reduces to the previous known results, which validates the correctness of our model. Our model can be applied in the seismic inversion of physical properties of reservoirs with intrinsic anisotropy, such as shale and tight sandstone reservoirs. In addition, our model can also be extended to cases with more complex intrinsic anisotropy and, thus, can be applied to complex anisotropic fractured reservoirs in the future. [ABSTRACT FROM AUTHOR]

S‐wave velocity plays a crucial role in various applications but often remains unavailable in vintage wells. To address this practical challenge, we propose a machine learning framework utilizing an enhanced bidirectional long short‐term memory algorithm for estimating S‐wave sonic logs from conventional logs, including P‐wave sonic, gamma ray, total porosity, and bulk density. These input logs are selected based on traditional rock physics models, integrating geological and geophysical relations existing in the data. Our study, encompassing 34 wells across diverse formations in the Delaware Basin, Texas, demonstrates the superiority of machine learning models over traditional methods like Greenberg–Castagna equations, without prior geological and geophysical information. Among these machine learning models, the enhanced bidirectional long short‐term memory model with self‐attention yields the highest performance, achieving an R‐squared value of 0.81. Blind tests on five wells without prior geologic information validate the reliability of our approach. The estimated S‐wave velocity values enable the creation of a basin‐scale S‐wave velocity model through interpolation and extrapolation of these prediction models. Additionally, the bidirectional long short‐term memory model excels not only in predicting S‐wave velocity but also in estimating S‐wave reflectivity for seismic amplitude variation with offset applications in exploration seismology. In conclusion, these S‐wave velocity estimates facilitate the prediction of further elastic properties, aiding in the comprehension of petrophysical and geomechanical property variations within the basin and enhancing earthquake hypocentral depth estimation. [ABSTRACT FROM AUTHOR]

Abstract This study integrates seismic inversion and rock physics techniques to evaluate the hydrocarbon potential of an offshore field in the Niger Delta. Five wells revealed three reservoir sands with favourable reservoir properties, including gross thickness (49.2–81.4 m), porosity (0.18–0.2), permeability (565–1481 mD), and water saturation (0.16–0.54). A robust wavelet extraction process was implemented to guide seismic inversion, and a well log-centric approach was employed to validate the resulting acoustic impedance data. Rock physics analysis established correlations between acoustic impedance (Zp), porosity, fluid content, and lithology, enabling the identification of hydrocarbon-filled sands, brine-saturated sands, and shales. These relationships enabled the discrimination of hydrocarbon-filled sands [5000–8000 (m/s)(g/cc)], from brine-saturated sands [5600–8400 (m/s)(g/cc)], and shales [5000–9000 (m/s)(g/cc)] within the inverted seismic data. The inverted acoustic impedance section showed a general increase with depth, reflecting the typical compaction effects in the Niger Delta. Analysis of the impedance distribution across horizon time slices revealed prospective zones with low impedance values [below 6300 (m/s)(g/cc)], particularly in horizons 1 and 2. These newly identified zones exhibit the strongest potential for hydrocarbon accumulation and warrant further investigation. This study demonstrates the effectiveness of using well log and rock physics constrained seismic inversion for hydrocarbon exploration in an offshore field in the Niger Delta.

The data driven approach to predict specific log/s from available data is essential when there are log gaps due to operational issues. The imputation at missing interval is crucial for rock physics modeling or synthetic seismic tie, as those studies require complete log. The artificial intelligence techniques such as random forest (RF) or artificial neural network (ANN) are effective to predict log from available log data. These algorithms have the advantages like scalability, liner/non-linear correlation between input logs, less chance of model overfitting, robust architecture, efficiency to reduce loss function etc. The selection of the best algorithm for specific area requires multiple testing of the predicted values. In this study, random forest and artificial neural network algorithms are used to predict sonic logs at missing intervals of approximately 20 m. As the missing interval covers reservoir zone, it poses limitation to carry out reservoir characterization and geomechanical modeling at the interval. The dataset for training and testing intervals was selected based on the quality of the data and geological input. The optimized hyper parameters were listed for both algorithms. To capture the uncertainties associated with the predicted sonic log from random forest, quantile percentage error was calculated. The residual errors like Mean Average Percentage (MAPE) and Root Mean Square Error (RMSE) were calculated on training data. The MAPE and RMSE errors are within an acceptable range, which are 1-2.5 and 0.01 respectively. The predicted sonic logs were plotted in velocity-porosity space with existing rockphysics model lines. It showed the value range of 2000–2300 m/s. The plot depicts that the ANN predicted values fall better on friable sand line compared to RF. Also, in the synthetic- seismic tie, the ANN output shows better correlation (~ 70%) than with RF output (~ 63%). The study shows a pragmatic approach to apply artificial intelligence techniques to train available log data for prediction of sonic log and further applications in rock physics model, geomechanical model and synthetic seismic correlation. [ABSTRACT FROM AUTHOR]

We exploit nonlinear elastodynamic properties of fractured rock to probe the micro‐scale mechanics of fractures and understand the relation between fluid transport and fracture aperture under dynamic stressing. Experiments were conducted on rough, tensile‐fractured Westerly granite subject to triaxial stresses. We measure fracture permeability for steady‐state fluid flow with deionized water. Pore pressure oscillations are applied at amplitudes ranging from 0.2 to 1 MPa at 1 Hz frequency. During dynamic stressing we transmit ultrasonic signals through the fracture using an array of piezoelectric transducers (PZTs) to monitor evolution of interface properties. We examine the influence of fracture aperture and contact area by conducting measurements at effective normal stresses of 10–20 MPa. Additionally, the evolution of contact area with stress is characterized using pressure sensitive film. These experiments are conducted separately with the same fracture and map contact area at stresses from 9 to 21 MPa. The measurements are a proxy for "true" contact area for the fracture surface and we relate them to elastic properties using the calculated PZT sensor footprints via numerical modeling of Fresnel zones. We compare the elastodynamic response of the fracture using the stress‐induced changes in ultrasonic wave velocities for transmitter‐receiver pairs to image spatial variations in contact properties. We show that nonlinear elasticity and permeability enhancement decrease with increasing normal stress. Additionally, post‐oscillation wave velocity and permeability exhibit quick recoveries toward pre‐oscillation values. Estimates of fracture contact area (global and local) demonstrate that the elastodynamic and permeability responses are dominated by fracture topology. Plain Language Summary: We perform laboratory experiments with fractured rock to understand the relation between fluid flow, fracture openness, and elastic properties under oscillating stresses. These experiments are conducted on rough, pre‐fractured granite specimens under normal stress conditions similar to those found in the shallow earth, a few kilometers in depth. Fluid pressure in the fracture is oscillated at various amplitudes at a fixed frequency. During this dynamic stressing, we use an ultrasonic device to monitor the evolution of the fracture interface. We examine the influence of fracture aperture and contact area by conducting measurements at increasing normal stress state. Additionally, the evolution of contact area with stress is characterized using pressure sensitive film, showing an image of where the two halves of the fracture are in contact. The ultrasonic monitoring reveals spatial variations in contact properties, which is informed by fracture contact area measurements. These measurements are also related to the fluid‐flow in response to dynamic stressing and similar comparisons are made for how the fracture interface evolves, recovers, following the stress perturbations. Key Points: Lab experiments to simulate fracture processes under dynamic stressingSimultaneous measurements of fluid flow and elastic wave properties to quantify elastodynamic and hydraulic responses to dynamic stressingLocal fracture aperture, not necessarily the stress state, dominates elastic and hydraulic responses to dynamic stressing [ABSTRACT FROM AUTHOR]

A comprehensive drilling of wells has been conducted in the Permian Qixia Formation in the central Sichuan Basin, revealing a significant number of dolomite reservoirs. High- and medium-porosity dolomite reservoirs are the main gas-producing reservoirs in the Qixia Formation. Seismic PP-wave data show a "bright spot" for high-porosity dolomite reservoir formations but weak responses for medium-porosity dolomite reservoir formations, which is attributed to the inability of P waves to distinguish between medium-porosity reservoirs and limestone. However, medium-porosity dolomite and limestone have different S-wave velocities. Therefore, in this study, the identification of different-porosity dolomite reservoirs using multi-component seismic data was investigated. A comprehensive analysis of the elastic waves by forward modeling shows that the PS-wave amplitude is more sensitive to medium-porosity dolomite than the PP-wave amplitude. Therefore, medium-porosity dolomite reservoirs can be predicted using the amplitude attributes of the PS-wave, and high-porosity dolomite reservoirs can be characterized using the PP-wave. Meanwhile, the elastic parameter λρ (the product of Lame constant λ and density ρ), which is highly correlated with the dolomite content, can be used as an indicator of dolomite formations. Furthermore, compared to the results of PP-wave inversion, the elastic parameters derived from the joint inversion of PP- and PS-waves exhibited a better correspondence with the well-logging results. The comprehensive use of the seismic amplitude responses of PP- and PS-waves and multi-component seismic joint inversion can effectively predict high- and medium-porosity dolomite reservoirs. The predicted results can support the exploration and development of the Qixia Formation. [ABSTRACT FROM AUTHOR]

A solid phase of natural gas hydrates can form from dissolved gas in oil during cold water injection into shallow undersaturated oil reservoirs. This creates significant risks to oil production due to potential permeability reduction and flow assurance issues. Understanding the conditions under which gas hydrates form and their impact on reservoir properties is important for optimizing oil recovery processes and ensuring the safe and efficient operation of oil reservoirs subject to waterflooding. In this work, we present two fluid displacement experiments under temperature control using Bentheimer sandstone core samples. A large diameter core sample of 3 inches in diameter and 10 inches in length was instrumented with multiphysics sensors (i.e., ultrasonic, electrical conductivity, strain, and temperature) to detect the onset of hydrate formation during cooling/injection steps. A small diameter core sample of 1.5 inches in diameter and 12 inches in length was used in a coreflooding apparatus with high-precision pressure transducers to determine the effect of hydrate formation on rock permeability. The fluid phase transition to solid hydrate phase was detected during the displacement of live-oil with injected water. The experimental procedure consisted of cooling and injection steps. Gas hydrate formation was detected from ultrasonic measurements at 7 °C, while strain measurements registered changes at 4 °C after gas hydrate concentration increased further. Ultrasonic velocities indicated the pore-filling morphology of gas hydrates, resulting in a high hydrate saturation of theoretically up to 38% and a substantial risk of intrinsic permeability reduction in the reservoir rock due to pore blockage by hydrates. [ABSTRACT FROM AUTHOR]

Geophysical subsurface characterization plays a key role in the success of geologic carbon sequestration (GCS). While deterministic inversion methods are commonly used due to their computational efficiency, they often fail to adequately quantify the model uncertainty, which is essential for informed decision‐making and risk mitigation in GCS projects. In this study, we propose the SVGD‐AE method, a novel geostatistical inversion approach that integrates geophysical data with prior geological knowledge to estimate subsurface properties. SVGD‐AE combines Stein Variational Gradient Descent (SVGD) for sampling high‐dimensional distributions with an autoencoder (AE) neural network for re‐parameterizing reservoir models, aiming to accurately preserve geologic characteristics of reservoir models derived from prior knowledge. Through a synthetic example of pre‐stack seismic inversion, we demonstrate that the SVGD‐AE method outperforms traditional probabilistic methods, particularly in inverse problems with complex posterior distributions. Then, we apply the SVGD‐AE method to the Illinois Basin—Decatur Project (IBDP), a large‐scale CO2 storage initiative in Decatur, Illinois, USA. The resulting petrophysical models with quantified uncertainty enhance our understanding of subsurface properties and have broad implications for the feasibility, decision making, and long‐term safety of CO2 storage at the IBDP. Plain Language Summary: Geologic carbon sequestration (GCS) provides a promising solution to mitigate the adverse effects of human‐generated CO2 emissions on the climate. GCS involves capturing CO2 emitted from industrial activities, such as those from coal‐fired power plants, and storing it deep underground. This procedure effectively prevents gas from entering the atmosphere and contributing to global warming. To ensure the success and safety of GCS projects, it is crucial to have a comprehensive understanding of the subsurface, including rock and fluid properties. In this research, we present an innovative probabilistic approach for quantifying subsurface properties using geophysical data. The proposed methodology has been successfully applied to the Illinois Basin—Decatur Project (IBDP), which is a large‐scale CO2 storage initiative in Decatur, Illinois, USA. Our study enhances the comprehension of subsurface attributes and supports informed decision‐making regarding the long‐term safety of CO2 storage at the IBDP. Key Points: A geostatistical inversion method is developed by integrating Stein variational gradient descent with autoencoderThe developed method provides an efficient approach for accurate subsurface characterization with uncertainty quantificationAn integrated reservoir characterization of the Mount Simon Sandstone at the Illinois Basin—Decatur Project is presented [ABSTRACT FROM AUTHOR]

Organic‐rich shales contain large amounts of oil and gas and are anisotropic because of fine‐scale layering and the partial alignment of organic matter and anisotropic clay minerals with the bedding. An example is the Wolfcamp Shale in the Permian Basin. Elastic anisotropy needs to be accounted for in the characterization of such formations using seismic data and plays a role in hydraulic fracturing and in the evaluation of stress changes and geomechanical effects resulting from production. Using extensive well log data acquired in the Midland Basin, the eastern sub‐basin of the Permian Basin, we estimate and compare the elastic anisotropy in the Middle and Upper Wolfcamp Shale by combining data from a vertical pilot well with two lateral wells, one (6SM) drilled in the Middle Wolfcamp and one (6SU) drilled in the Upper Wolfcamp. The data used were acquired at the Hydraulic Fracture Test Site 1, located in the eastern part of the Midland Basin. Thomsen's anisotropy parameter γ$\gamma $ calculated from the fast and slow shear sonic is higher on average for the 6SM lateral than for 6SU, consistent with there being less carbonate content in 6SM than in 6SU. However, the anisotropy parameter γ$\gamma $ in some regions with higher carbonate content in well 6SU is higher than in well 6SM. This may indicate the influence of natural fractures. The primary set of steeply dipping fractures observed in the lateral wells at Hydraulic Fracture Test Site 1 acts to increase γ$\gamma $ if the ratio of the normal‐to‐shear fracture compliance is less than about 0.5. Sub‐horizontal fractures may also increase γ$\gamma $ and could affect the vertical extent of hydraulic fractures. Relations between elastic moduli C33 and C55 in the Upper and Lower Wolfcamp in a vertical pilot well allow C33 to be predicted in a lateral well using measurements of C55 in that well. Comparison of Thomsen's anisotropy parameters γ$\gamma $ and ε$\varepsilon $, with γ$\gamma $ calculated from the measured values of C55 and C66 and ε$\varepsilon $ calculated from the measured values of C11 and predicted values of C33, show that ε$\varepsilon $ is mostly greater than γ$\gamma $. [ABSTRACT FROM AUTHOR]

Predicting the water abundance of coal‐bearing strata is crucial for ensuring mining safety. However, owing to the dispersion and attenuation characteristics caused by pore fluid flow, it is difficult to estimate the water abundance of coal seam roof aquifers using seismic data. To overcome this challenge, we provide the relationship between the frequency‐dependent seismic wave velocity and water saturation based on the Chapman fracture model and the mixing fluid model. We propose a seismic dispersion attribute technique that can use dispersion information as an indicator of water abundance. Numerical experiment results show that the water saturation of the sandstone aquifer is positively correlated with the dispersion attribute. The results of low‐frequency rock physical experiments are roughly consistent with those predicted by the model for the given parameters. Using seismic dispersion attribute inversion and the frequency slice wavelet transform method, we predicted the water abundance of sandstone in the coal seam roof of the Yuwang coal mine in Yunnan Province, China. The predicted sandstone water abundance was compatible with the actual water‐rich scenario observed in well logs and downhole drilling in the study area. Therefore, the method proposed herein has the potential to quantitatively determine the water abundances of sandstone aquifers in coal seam roofs. [ABSTRACT FROM AUTHOR]

Coalbed methane is a hot spot for gas exploration at present, and fractures are widely developed in the coals. However, despite being essential for a number of geophysical applications such as reservoir prediction and hydraulic fracturing, the influence of fractures on the elastic properties and anisotropy of coals is still poorly understood. Therefore, three groups of cylindrical coals were drilled along the face and butt cleat directions to study the effects of pressure and fracture on the elastic properties and anisotropy of tectonic coals. The velocity along the face cleat direction is less sensitive to the pressure than that along the butt cleat direction due to the difference in compliant pore and fracture content. Coals display a strong directional dependence in petrophysical and elastic properties. The permeabilities and velocities of samples along the butt cleat direction are much lower than those along the face cleat direction. The fracture densities are quantitatively characterized by the theoretical model. The values along the face cleat direction are much smaller than those along the butt cleat direction. The influence of fractures on the elastic properties and anisotropy is comprehensively studied by theoretical and laboratory methods. The mineralogy and fracture effects are important factors to the elastic anisotropy of coals, the latter can be a dominant factor to the coal elastic anisotropy. The results can contribute to the understanding of the cleat system of coalbed methane reservoir and can provide a critical rock physics basis for micro‐seismic fracture monitoring and reservoir prediction. [ABSTRACT FROM AUTHOR]

Material density remains poorly constrained in seismic imaging problems, yet knowledge of density would provide important insight into physical material properties for the interpretation of subsurface structures. We test the sensitivity to subsurface density contrasts of spatial and temporal gradients of seismic ambient noise wavefields, using wave equation inversion (WEI), a form of seismic gradiometry. Synthetic results for 3-D acoustic media suggest that it is possible to estimate relative density structure with WEI by using a full acoustic formulation for wave propagation and gradiometry. We show that imposing a constant density assumption on the medium can be detrimental to subsurface seismic velocity images. By contrast, the full acoustic formulation allows us to estimate density as an additional material parameter, as well as to improve phase velocity estimates. In 3-D elastic media, severe approximations in the governing wave physics are necessary in order to invert for density using only an array of receivers on the Earth's free surface. It is then not straightforward to isolate the comparatively weak density signal from the influence of phase velocity using gradiometric WEI. However, by using receivers both at the surface and in the shallow subsurface we show that it is possible to estimate density using fully elastic volumetric WEI. [ABSTRACT FROM AUTHOR]

The strong sensitivity of velocity to stress observed in many sandstones originates from the response of stress‐sensitive discontinuities such as grain contacts and microcracks to a change in effective stress. If the change in stress is anisotropic, then the change in elastic wave velocities will also be anisotropic. Characterization of stress‐induced elastic anisotropy in sandstones may enable estimation of the in situ three dimensional stress tensor with important application in solving problems occurring during drilling, such as borehole instability, and during production, such as sanding and reservoir compaction. Other applications include designing hydraulic fracture stimulations and quantifying production‐induced stresses which may lead to rock failure. Current methods for estimating stress anisotropy from acoustic anisotropy rely on third‐order elasticity, which ignores rock microstructure and gives elastic moduli that vary linearly with strain. Elastic stiffnesses in sandstones vary non‐linearly with stress. Using P‐ and S‐wave velocities measured on Gulf of Mexico sandstones, this non‐linearity is found to be consistent with a micromechanical model in which the discontinuities are represented by stress‐dependent normal and shear compliances. Stress‐induced anisotropy increases with increasing stress anisotropy at small stress but then decreases at larger stresses as the discontinuities close and their compliance decreases. When the ratio of normal‐to‐shear compliance of the discontinuities is unity, the stress‐induced anisotropy is elliptical, but for values different from unity, the stress‐induced anisotropy becomes anelliptic. Although vertical stress can be obtained by integrating the formation's bulk density from the surface to the depth of interest, and minimum horizontal stress can be estimated using leak‐off tests or hydraulic fracture data, maximum horizontal stress is more difficult to estimate. Maximum horizontal stress is overpredicted based on third‐order elasticity using measured shear moduli, with estimates of pore pressure, vertical stress and minimum horizontal stress as input. The non‐linear response of grain contacts and microcracks to stress must be considered to improve such estimates. [ABSTRACT FROM AUTHOR]

Digital rock physics is a workflow that relies on imaging techniques to quickly and cost‐effectively estimate the petrophysical properties of small core samples taken from reservoirs. By using digital representations of rock samples as input, physics‐based simulators can estimate properties such as porosity and permeability. The accuracy of these estimates depends on the quality of the digital volumes generated from micro‐computed tomography scans. To enhance the accuracy, denoising is necessary to reduce image noise caused by various experimental factors like electronic noise and bad pixels. This study introduces a novel two‐step denoising pipeline that combines adaptive morphological filtering with non‐local means smoothing, ensuring both noise reduction and preservation of edges. The effectiveness of the proposed pipeline is assessed through qualitative evaluation using optimal segmentation results and quantitative evaluation using a non‐reference metric and equivalent number of looks. Comparing the results of the two‐step approach with traditional non‐local means and morphology‐based filtering using a multi‐resolution structurally varying bitonic filter, the non‐reference metric and equivalent number of looks values are higher, indicating improved denoising performance. Furthermore, the denoised rock volume is subjected to the next step in the digital rock workflow to compute important petrophysical properties like porosity and permeability. The findings indicate that our proposed pipeline significantly improves the accuracy of estimating physical parameters such as porosity and permeability. [ABSTRACT FROM AUTHOR]

Coal seams exhibiting nearly horizontal bedding, and fractures can be characterized as transversely isotropic media with a vertical axis of symmetry, known as vertical transverse isotropy coal seams. The resulting anisotropy cannot be overlooked in high‐precision seismic velocity analysis, migration imaging and pre‐stack inversion. Therefore, we estimate the anisotropy of the vertical transverse isotropy coal seam (using the anisotropic Thomsen's parameters ε, γ and δ) by inverting the horizontal P‐ and SH‐wave velocities and fracture density based on a rock physics model. The Mori–Tanaka model and Brown–Korringa formula were first used to quantify the anisotropy of the vertical transverse isotropy coal seams impacted by dry and fluid‐saturated fractures. Subsequently, we formulated an equation for the inversion of horizontal P‐ and SH‐wave velocities, considering the measured vertical P‐ and SH‐wave velocities as constrained parameters. This approach is generally applied in vertical drilling scenarios. We tested the inversion method using the ultrasonic test results of coal samples collected from the southern margin of the Qinshui Basin, China and then used it on the full waveform logging data from a vertical coalbed methane well. Both the inversion results of horizontal P‐ and SH‐wave velocities and the estimated anisotropic parameters (ε and γ) were in good agreement with the ultrasonic test results of coal samples, although the accuracy of δ was slightly lower. Therefore, we believe that the proposed method can be extended to estimate the anisotropy of vertical transverse isotropy medium (assuming suitable rock physics models) for the ultrasonic testing of rock samples and full waveform logging along the vertical direction in near‐horizontal formations. [ABSTRACT FROM AUTHOR]

Wave‐induced fluid flow is considered to be a major source of seismic attenuation and dispersion in porous rocks. From the physical description of partially saturated reservoirs, numerous analytical solutions based on upscaling homogenization theories have been employed to calculate equivalent frequency‐dependent poroelastic media. Nevertheless, dispersion and attenuation predictions are often not reasonably consistent with laboratory and field measurements in a broad frequency range, particularly due to influences of biphasic fluids and their distribution, presence of heterogeneities on various length scales, and pore microstructure. We investigate the role of pore microstructure on pressure and fluid saturation dependence of elastic velocities in tight sandstones. Previous work points out that differentiating the impacts of heterogeneities at various scales on dispersion within seismic exploration and sonic frequencies can be very difficult. In practice, this is because fluid‐related dispersion mechanisms are impossible to be independent. Thus, it is important for a theoretical and more quantitative analysis of the relative contribution of interrelated energy dissipation processes through a better understanding of combined influences due to the presence of microscopic and mesoscopic heterogeneities. Based on microscopic squirt flow and mesoscopic flow in a partially saturated medium, we develop a poroelastic model that allows evaluating the overall frequency‐dependent dispersion via considering a random distribution of fluid heterogeneities as well as the broadly distributed aspect ratio of compliant pores. Experimental validation of the model is accomplished via a comprehensive comparison of predictions with measurements of partially saturated velocities versus pressure and fluid for sandstones with specific pore microstructures. [ABSTRACT FROM AUTHOR]

We propose an approach for measuring seismic attenuation at ultrasonic frequencies on laboratory‐scale samples. We use a Gaussian filter to select a bandwidth of frequencies to identify the attenuation in a small window and, by moving the window across the frequency content of the data, we determine the frequency‐dependent attenuation function. We assess the validity of the method with three‐dimensional numerical simulations of seismic wave propagation across different sample geometries, using free surface boundary conditions. We perform the simulations using viscoelastic media under various seismic attenuation models. Our numerical results indicate that we can successfully recover the representative viscoelastic attenuation parameters of the media, regardless of the sample geometry, by processing the seismic signal recorded either within the volume or at the boundaries. Due to the equipartition phenomenon, the energy of S‐waves is consistently higher in seismic records than that of P‐waves. Therefore, we systematically recover the attenuating properties of S‐waves in the medium. We also conduct experiments of seismic wave propagation on samples of aluminum and Fontainebleau sandstone to validate our approach with real data. The quality factor of the S‐wave Qs$Q_s$ in the aluminum medium increases from 300 to 7000 between 60 kHz and 1.2 MHz. The Fontainebleau sandstone, which is more attenuating, exhibits a Qs$Q_s$ that increases from 200 at 60 kHz to 1000 at 1.2 MHz. With our approach, we are not only able to recover the attenuation property but also identify the frequency‐dependent attenuation model of the samples. Our method allows for seismic attenuation recovery at ultrasonic frequencies in low‐attenuating media. [ABSTRACT FROM AUTHOR]

Attenuation is an essential reservoir property, and understanding its mechanism in gas hydrate-bearing sediments is important for predicting gas hydrate saturation. Natural gas hydrates mainly accumulate in coarse-grained sands or fine-grained clays with different morphologies, and the attenuation characteristics of these gas hydrate-bearing sediments are inconsistent. Many rock-physics models have been proposed in recent years to elucidate the attenuation mechanisms of gas hydrate occurrence. There are two types of attenuation models for gas hydrates in sands. One of these models is based on the three-phase Biot theory and contains multiple mechanisms that describe the contact effects between hydrate and sediment grains, such as grain cementation and squirt flows caused by microcracks. This model can reasonably reproduce the enhanced attenuation observed with increasing hydrate saturation in sonic-logging data. Attenuation described in the effective grain model is dominated by the viscous flow between the water in hydrate pores and free water. These types of models agree with the seismic attenuation observed in gas hydrates in sands. Moreover, the attenuation model of gas hydrates in clay is formulated by first establishing an attenuation model for background sediments, which employs the effective grain model to characterize attenuation in clay minerals; then, the properties of pure gas hydrate and the effects of hydrate occurrence on sediments are quantified. This model has also been successfully applied to seismic reflection data in the seismic frequency band. The above models have achieved significant progress in attenuation studies on gas hydrate-bearing sediments, and they have aided the quantitative interpretation of observed attenuation in field data and attenuation-related constraints for gas hydrate saturation. However, the application of these models is limited to certain extents: the attenuation predicted by the gas hydrate-bearing sands model failed to match that observed in the field data. Additionally, the gas hydrate-bearing clays model does not consider fracture shapes, and its performance has not been verified at the ultrasonic frequency band. To improve the accuracy and applicability of these models, the relationship between hydrate morphology and attenuation must be elucidated, and further rock-physics studies based on field data must be conducted.

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We develop a method to estimate relative seismic moments M0 and corner frequencies fc of acoustic emission events recorded in laboratory experiments from amplitude spectra of signal's coda composed of reverberated and scattered waves. This approach has several advantages with respect to estimations from direct waves that are often clipped and also are difficult to separate in experiments performed on small samples. Also, inversion of the coda spectra does not require information about the source locations and mechanisms. We use the developed method to analyze the data of two experiments: (a) on granite from the Voronezh crystal massif and (b) on Berea sandstone. The range of absolute corner frequencies estimated in both experiments is around 70 − −700 kHz. The range of relative seismic moments covers 103.5. The relation between fc and M0 observed on the first stages of both experiments, consisted of increasing isotropic confining pressure, approximately follow M0∼fc−3 ${M}_{0}\sim {f}_{c}^{-3}$ scaling and the b‐value of the Gutenberg‐Richter distribution was found close to 1. This can be interpreted as rupturing of preexisting material defects with a nearly constant stress‐drop and has a similarity with observations of "natural" earthquakes. Deviations from this "earthquake‐like" behavior observed after applying axial loading and initiation of sample damaging can be interpreted as changes in stress‐drop. Lower stress‐drops prevail for sandstone and higher for granite sample respectively that can be related to the strength of corresponding material. Plain Language Summary: Earthquakes generation mechanisms and conditions favoring their occurrence are still debated. Inability to observe these processes in–situ and long lasting earthquake preparation period favor using laboratory experiments to verify quickly the adequacy of proposed hypotheses. Fracturing of small rock samples with high pressures and recording acoustic waves from their micro‐fractures is among them. In most cases, the laboratory acoustic emission (AE) is analyzed and compared to natural seismicity statistically, demonstrating similar Gutenberg‐Richter power‐law magnitude distribution. More advanced analyses can include source characteristics (corner frequencies, seismic moments, and stress‐drops), responsible for the source size, forces acting there and stress changes. Ensembles of these characteristics can give ideas on the common generation mechanisms. In laboratory, several technical limitations slow down the implementation of such analyses, widely used in Earth's seismology. We propose a method that use coda waves (signal's decaying part) to estimate source parameters of the laboratory AE. We tested it on two similar experiments conducted on different rock types. Source analyses revealed the high similarity of well‐studied tectonic earthquakes and fracturing of pre‐existing inhomogeneties in the rock samples by applying equally distributed external pressure to it. The active production of new fractures under high one‐directional pressure in contrary deviated significantly. Key Points: Coda of acoustic emission (AE) waveforms can be used for the source characterizationScaling between the corner frequency fc and seismic moment M0 varies in function of loading regime and rock typeThe M0 − fc scaling of AE events was found similar to that of tectonic earthquakes when isotropic confining pressure applied to intact rocks [ABSTRACT FROM AUTHOR]

In many subsurface studies, facies and petrophysical properties are two important reservoir parameters that are closely correlated. They are routinely used in well interpretation, hydrocarbon reserve calculation and production profile prediction. These two parameters have commonly been determined in two separate tasks because of their mathematical differences (facies are discrete, and petrophysical properties are continuous). However, this is incorrect because facies and petrophysical properties are often strongly correlated. Therefore, we propose a new joint inversion method of facies and petrophysical properties based on a bi‐level optimization model. In the bi‐level optimization model, the upper‐level problem is the petrophysical property inversion while the lower‐level problem can identify the facies and add a facies‐related constraint for the upper‐level optimization. We also develop a new genetic algorithm for the discrete‐continuous inversion problem based on the bi‐level optimization model because the inversion problem usually has multiple local solutions. In addition, rock physics and statistics are combined in the inversion process. A rock physics model is used to establish the basic relationships between the petrophysical and elastic parameters, and the statistical approach is used to describe the intrinsic connection among the multiple reservoir parameters based on well log data. The numerical experiments indicate that the traditional separate prediction method and the new joint inversion method can quickly obtain more accurate results. In the application examples of real data, the inversion results can be matched to the well log data within the limits of the input data resolution, which further verifies the reliability and application potential of this new method. [ABSTRACT FROM AUTHOR]

The formations above a producing reservoir can exhibit large mechanical changes, creating a risk of significant subsidence and loss of rock integrity. These changes can be monitored by time‐lapse seismic acquisition, which measures the corresponding velocity changes via time‐shifts. Third‐order elastic theory can be used to connect subsurface strains and stress changes to these seismic attribute changes. Existing models assume isotropic strain dependence of the dynamic stiffness in shales. It is important to re‐evaluate this isotropic assumption considering the inherent anisotropy of shales and their abundance in the overburden. Thus, we instead propose a third‐order elastic model with a transversely isotropic strain dependence of the dynamic stiffness. When calibrated, this new model satisfactorily predicted P‐wave velocity changes determined in undrained laboratory experiments conducted on overburden field shales, covering a wide range of propagation directions and stress variations. The shales exhibit anisotropic dynamic strain sensitivity, resulting in a significantly higher strain sensitivity predicted for Thomsen's anisotropy parameters epsilon and delta subjected to a uniaxial strain parallel to the horizontal bedding plane compared to the vertical direction. Geomechanical modelling, considering a depleting disk‐shaped reservoir surrounded by shales, was employed to predict the dynamic stiffness changes of the overburden using the laboratory‐calibrated third‐order elastic model. The overburden time‐shifts increased with offset angle, peaking at about 45°, suggesting a strong influence of shear strains on the time‐shifts. In contrast, a corresponding model with an isotropic third‐order elastic tensor, calibrated to the same data, exhibited a significantly lower sensitivity to the shear strains. These results underscore the importance of considering the anisotropic strain dependence of the dynamic stiffness when studying shales. Interpreting offset‐dependent trends in pre‐stack time‐lapse seismic data, along with geomechanical modelling and an appropriate strain‐dependent rock physics model, can assist in quantifying subsurface strains and stress changes. [ABSTRACT FROM AUTHOR]

The presence of sets of vertical, parallel fractures is very common in the Earth's upper crust. Notably, open fractures exert critical control on the mechanical and hydraulic properties of the host formation. There is great interest in understanding how fractures interact with seismic waves, as this knowledge could be used to detect and characterize fractures from seismic data. When a seismic wave travels through a fractured formation, it induces oscillatory fluid pressure diffusion between the fractures and the embedding porous background, a physical process that produces attenuation and dispersion of the seismic wave. Although there are numerous studies on this topic, the case of parallel fractures saturated with different immiscible fluids, such as brine and CO2, remains rather unexplored. With these motivations, in this work, we propose an analytical approach to compute the phase velocity and attenuation of P‐waves travelling perpendicularly to a set of planar, parallel fractures. While we consider that the background is saturated with brine, the fractures can be saturated with brine or gas. Our numerical analysis shows for the first time that two manifestations of fluid pressure diffusion arise in these cases. One of them, associated with relatively high levels of attenuation, is due to fluid pressure diffusion occurring between consecutive fractures saturated with different fluids. In this case, the fluid pressure diffusion process is initiated at a fracture saturated with brine and reaches a consecutive fracture saturated with gas. The other fluid pressure diffusion manifestation, on the other hand, arises at higher frequencies, is characterized by lower levels of attenuation and results from the interaction in the background of fluid pressure diffusion processes initiated at consecutive fractures, irrespective of the fluid content. Finally, by considering a stochastic distribution of the two fluids and a classical frequency of interest in seismic experiments, we obtain P‐wave attenuation and phase velocity as functions of the fracture gas saturation. This approach could be of interest for the remote detection and quantification of pore fluids using seismic waves. [ABSTRACT FROM AUTHOR]

Reservoir prediction and prospectivity are performance indices of the oil and gas field development planning and reserves estimation which depicts the behaviour of the reservoir in the future; its success is dependent on accurate description of the reservoir rock properties, fluid properties, rock-fluid properties and flow. Hence, the objective of this paper was to investigate and predict the reservoir and prospectivity of Omos Field, Onshore Niger Delta Basin, by integrating appropriate standard methods. Results obtained from rock physics attribute map analysis revealed very high Mu-Rho values between 13.0-16.2 Gpa, that is expected for sand presence, and this agrees with the good quality reservoir sands predicted from sequence stratigraphy study.Lambda-Rho values obtained ranges between - 1 to 9.5 GPa, with a much lower value between -1 to 4.3 in the prospective zone that indicates the presence of hydrocarbon bearing sand. These results agree with the results of structural and amplitude maps analysis. Hence the prospective reservoir has a very good hydrocarbon potential in this zone and should be a target for further appraisal for development and production purposes [ABSTRACT FROM AUTHOR]

Seismic inversion is the primary way to obtain subsurface models, lithologic and stratigraphic information. However, seismic elastic parameters inversion and 'discrete lithofacies' identification for complex volcanic reservoirs are usually independent during the whole inversion process. Also, the influence of reservoir lithology on elastic parameters is not always considered directly before lithofacies prediction. This paper proposes a probabilistic pre-stack seismic inversion method for lithofacies and elastic parameters of volcanic reservoirs. Under the framework of Bayesian inversion, considering that the prior probability distribution of elastic parameters of volcanic reservoirs is affected by volcanic lithofacies, a posteriori probability distribution characterized by a mixed probability model is first derived. Then, a single-point-direct sequential simulation stochastic algorithm with simultaneous optimization of multiple solutions is used to simulate the posterior probability distribution of elastic parameters and lithofacies of volcanic reservoirs, which improves the resolution of lithofacies prediction results of volcanic reservoirs. The feasibility and stability of our method are ensured through synthetic and field applications. The prediction results highly agree with logging curves and lithology logging interpretation data. We have improved the resolution of volcanic rock reservoir lithofacies prediction results. In one-dimensional tests, we achieved the prediction of lithofacies and elastic parameters for three types of volcanic lithofacies. The error compared to prior information is no higher than 15%, thereby verifying the method's good noise resistance. [ABSTRACT FROM AUTHOR]

Quantitative seismic methods are crucial for understanding shale gas reservoirs. This study introduces a dynamic adaptive rock physics model (DARPM) designed to systematically quantify the relationship between physical parameters and elastic parameters within shale formations. The DARPM uniquely adapts to changes in formation dip angle, allowing adaptive reservoir property assessment. An innovative adaptive rock physics inversion methodology is subsequently proposed to compute values for reservoir physical and seismic anisotropy parameters. This is achieved using well log data and building upon the foundation laid by the established DARPM. We introduce the RPM-FCNN (rock physics model—fully connected neural network) framework, seamlessly integrating the DARPM with the corresponding inversion results into a comprehensive model. This framework facilitates a quantitative analysis of the nonlinear relationship between elastic and reservoir physical parameters. Utilizing the trained RPM-FCNN framework, the spatial distribution of reservoir and seismic anisotropic characteristics can be precisely characterized. Within this framework, the organic matter mixture aspect ratio indicates the continuity of organic matter, while the organic matter porosity reveals the maturity of organic matter. Simultaneously, seismic anisotropy characteristics signify the degree of stratification within the reservoirs. This method, therefore, establishes a robust foundation for identifying favorable areas within shale gas reservoirs. [ABSTRACT FROM AUTHOR]

An accurate petrophysical model of the subsurface is essential for resource development and CO2 sequestration. We present a new workflow that provides a high-resolution estimate of petrophysical reservoir properties using seismic data with rock physics modeling and machine-learning techniques (i.e., deep learning neural networks). First, we compare the sequential prediction of the following petrophysical attributes: mineralogy, porosity, and fluid saturation, with the simultaneous prediction of all of the properties using the Volve field in the Norwegian North Sea as an example. The workflow shows that the sequential prediction produces a more efficient and accurate classification of petrophysical properties (the RMS error between the predicted and the original seismic trace is 50% smaller for the sequential compared to the simultaneous procedure). Next, the seismic amplitude response of the reservoirs was studied using rock physics modeling and amplitude versus offset (AVO) analysis to distinguish the different lithologies and fluid types. To ascertain the optimal hydrocarbon production areas, we performed Bayesian seismic inversion and applied machine learning to estimate the petrophysical properties. We examined how porosity, Vclay, and fluid variations affect the elastic properties. In Poisson's ratio versus the P-wave impedance domain, a 10% porosity increase decreases the acoustic impedance (AI) by 30%, while a 20% Vclay decrease increases the AI by 12%. The Utsira Formation in the Volve field (5 km north of the Sleipner Øst field) was evaluated as a potential CO2 geological storage unit using Gassmann fluid substitution and seismic modeling. We look to assess the elastic property variation caused by CO2 saturation changes for monitoring purposes and simulate the effect. In the first 10% CO2 substitution, the P-wave velocity decrease is 12%, a subtle effect is observed for higher CO2 saturation values, and S-wave velocity (Vs) increases with CO2 saturation. Our analysis aspires to assist future reservoir studies and CO2 sequestration in similar fields. [ABSTRACT FROM AUTHOR]

Knowledge about the seismic elastic modulus dispersion, and associated attenuation, in fluid-saturated rocks is essential for better interpretation of seismic observations taken as part of hydrocarbon identification and time-lapse seismic surveillance of both conventional and unconventional reservoir and overburden performances. A Seismic Elastic Moduli Module has been developed, based on the forcedoscillations method, to experimentally investigate the frequency dependence of Young's modulus and Poisson's ratio, as well as the inferred attenuation, of cylindrical samples under different confining pressure conditions. Calibration with three standard samples showed that the measured elastic moduli were consistent with the published data, indicating that the new apparatus can operate reliably over a wide frequency range of f=[1-2000, 106] Hz. The Young's modulus and Poisson's ratio of the shale and the tight sandstone samples were measured under axial stress oscillations to assess the frequency- and pressure-dependent effects. Under dry condition, both samples appear to be nearly frequency independent, with weak pressure dependence for the shale and significant pressure dependence for the sandstone. In particular, it was found that the tight sandstone with complex pore microstructure exhibited apparent dispersion and attenuation under brine or glycerin saturation conditions, the levels of which were strongly influenced by the increased effective pressure. In addition, the measured Young's moduli results were compared with the theoretical predictions from a scaled poroelastic model with a reasonably good agreement, revealing that the combined fluid flow mechanisms at both mesoscopic and microscopic scales possibly responsible for the measured dispersion. [ABSTRACT FROM AUTHOR]

Unconsolidated sandstones are attractive targets for underground storage of carbon due to their high porosity and permeability. Monitoring of injection and movement of CO2 in such formations using elastic waves requires an understanding of the acoustic properties of the sandstone. Current approaches often use the so‐called soft‐sand model in which a Hertz–Mindlin model of the acoustic properties at high porosity is mixed with the acoustic properties of the mineral phase to predict the acoustic properties over the entire porosity range. Using well‐log data from two unconsolidated sand formations of interest for CO2 storage, we discuss the limitations of this model and provide an alternative approach in which the mechanical properties of grain contacts are obtained by inversion, and the properties of infill material lying within the pore space are estimated. The formations considered are the Paluxy Formation in Kemper County, Mississippi, and the Frio Formation near Houston, Texas. The ratio of the normal to shear compliance of the grain contacts is found to be significantly less than unity for both formations. This implies that the grain contacts are more compliant in shear than in compression. However, the grain contact compliance is higher and the ratio of the normal to shear compliance is lower for the Frio example than for the Paluxy case, and this may lead to sliding at grain contacts with low shear compliance and transport of grains during fluid flow, particularly if CO2 acts to weaken any cement that may be present at the grain contacts. Such transport was suggested by Al Hosni et al. in explaining why the magnitude of the time‐lapse effect due to the injection of CO2 at the Frio CO2 injection site is greater than predicted using conventional rock physics models. A simple model of the mechanical properties of infill material lying within the pore space suggests that the bulk and shear moduli of infill material in the Paluxy case are significantly higher than the Frio case, consistent with the lower grain contact compliance in the Paluxy case. [ABSTRACT FROM AUTHOR]

Elastic wave velocities of compressional and shear waves propagating through sedimentary rocks are often coupled with information of bulk density to derive the rock stiffness. Acquiring the transit time of compressional and shear waves often involves manual picking of wave arrival times from wave trains recorded in the laboratory or by well‐logging tools. Picking the compressional wave arrival time is commonly accepted as straightforward. Oppositely, detecting the shear wave arrival and picking its arrival time is often troublesome because the transmitted shear wave partly converts to compressional waves and back to a secondary shear wave, concealing the transmitted shear wave arrival in the wave train. In laboratory settings, we illustrate the difficulty of shear wave detection in wave trains recorded on highly porous chalk plug samples from the Danish North Sea Basin. Wave trains were recorded on plugs dry, Tap‐water or Isopar‐L saturated during uniaxial strain compaction. The recorded shear wave trains showed two distinct features, which could be interpreted as the transmitted shear wave first arrival; we denoted them as early and late arrivals. However, as only one feature can mark the arrival of the transmitted shear wave, we propose a semi‐empirical disclosure strategy combining a graphical representation of stacked wave trains with rock physical modelling. By stacking recorded wave trains in a graphical strain–time–amplitude domain, we demonstrate that an early shear wave feature marks a converted shear to compressional to shear wave and not the transmitted shear wave. We used physical modelling to identify early shear wave features and illustrate the consequences of adopting a falsely interpreted shear wave on stiffness properties. [ABSTRACT FROM AUTHOR]

Coal elastic parameters are an important index reflecting the material composition and porosity, which can be used to guide reservoir evaluation and the safe mining of coal and coalbed methane. In this study, coal samples collected from coal seams #2, #3, #7 + 8 and #9 in the Yuwang colliery, eastern Yunnan, were studied, and the influences of organic matter, ash content and porosity on the elastic parameters of coal samples were investigated. The results show that the elastic parameters of coal are negatively correlated with organic matter content and porosity, and positively correlated with ash content. This means that the bulk modulus and primary‐wave velocity of coal decrease with a gradual increase in organic matter content or porosity and increase with a gradual increase in ash content. The main reason for this is that the ash modulus is typically higher than that of coal. When the ash content gradually increases, the contribution of ash to the equivalent modulus of coal increases, whereas the contribution of organic matter and pores decreases. In this study, the primary‐wave velocity of the target coal seam was fitted based on the generalized Gassmann equation. The calculation results were consistent with the observations and the relative error was within 7%. According to the distribution behaviour of elastic parameters, this provides adequate data support for the prediction of gas content in coal mines and ensures safe and green mining of coal resources. [ABSTRACT FROM AUTHOR]

Considerably different from sandstones, sands have point‐like contact of grains. In contrast, sandstones have cementation between grains, which has diminished the very narrow gap at contact of grains. In this paper, ultrasonic S‐wave in brine‐saturated glass beads and Ottawa sands is used to detect the very narrow space at contact of grains. The data of the dry beads/sands and brine are inputted into Biot theory to yield phase velocity of the saturated beads/sands. By fitting the theoretical velocity with the ultrasonic measurement, phase velocity, the quality factor and S‐wave permeability are determined as functions of frequency. The predicted ultrasonic quality factors appear to be very close to that of water‐saturated Berea sandstone. Our previous study showed that for Berea sandstone, the low‐frequency S‐wave permeability is approximately half of Darcy permeability. However, for glass beads and Ottawa sands, the S‐wave permeabilities at low frequencies are one‐order magnitude lower than Darcy permeabilities. This well shows that S‐wave permeability of the beads/sands is associated with the very narrow gap at contact of grains which is successfully detected by ultrasonic S‐wave in the indirect way. [ABSTRACT FROM AUTHOR]

Triaxial compression experiments were carried out on samples of fine‐grained Aji granite to measure the evolution of permeability during deformation prior to failure under confining pressures of 20 and 40 MPa. During the initial stages of deformation, a small decrease in permeability was observed, due to the closure of pre‐existing microcracks; permeability then increased with increasing differential stress. During deformation, permeability varied by up to two orders of magnitude, and we observed a small pressure dependence, with a larger variation observed at 20 MPa than at 40 MPa. This suggests that more cracks developed during brittle deformation under the lower confining pressure. The observed increase in permeability during our experiments was approximately proportional to inelastic volumetric strain, which corresponded to the volume of dilatant cracks. On the other hand, prior to brittle failure, we observed a further increase in permeability that was greater than the inelastic volumetric strain, suggesting crack aperture opening accelerated at this stress level (>∼80%). The permeability enhancement resulting from the crack dilation affects the gas‐sealing capacity of the fluid‐saturated caprock. Our experimental findings would be beneficial for the safety assessment in applications such as the long‐term storage of various gaseous wastes. [ABSTRACT FROM AUTHOR]

Microseismic monitoring is a promising method for the safety monitoring of underground mines. However, it is crucial to isolate microseismic signals related to the collapse of a mine from others for successful monitoring because the monitoring system records various signals. Recently, deep learning‐based classification techniques have achieved high performance in such data classification problems. In this context, we develop an automatic signal classification technique using the modified WaveNet classifier. The main characteristic of the WaveNet structure is its ability to extract features at various frequencies from very long time‐series data, and such an advantage makes the WaveNet suitable for seismic data processing. The data imbalance problem coming from the safe condition of the monitoring target is solved by augmenting the training data with those acquired from another mine and employing class weighting. After training, an optimal classifier is chosen considering the loss function, accuracy and Fβ score. The optimal classifier shows very high accuracy and excellent performance for the test data prediction. Compared to the random forest model and another one‐dimensional convolutional neural network–based network, the suggested classifier has higher reliability in predicting microseismic signals. Even though the proposed WaveNet model has a much more complex structure than the random forest model, the actual application examples demonstrate that the proposed model achieves high efficiency without any preprocessing. The automatic signal classifier developed in this study can be directly applied to various safety monitoring problems, not only mines, to improve the efficiency and reliability of monitoring systems. [ABSTRACT FROM AUTHOR]

Fluid flow and pore‐pressure cycling are believed to control slow slip events (SSEs), such as those that frequently occur at the northern Hikurangi margin of New Zealand. To better understand fluid flow in the forearc system we examined the relationship between several physical properties of Cretaceous‐to‐Pliocene sedimentary rocks from the Raukumara peninsula. We found that the permeability of the deep wedge is too low to drain fluids, but fracturing increases permeability by orders of magnitude, making fracturing key for fluid flow. In weeks to months, plastic deformation, swelling, and possibly not‐yet‐identified mechanisms heal the fractures, restoring the initial permeability. We conclude that overpressures at the northern HM might partly dissipate during SSEs due to enhanced permeability near faults. However, in the months following an SSE, healing in the prism will lower permeability, forcing pore pressure to rise and a new SSE to occur. Plain Language Summary: Earth's crust comprises many tectonic plates fitting together like jigsaw puzzle pieces. Tectonic plates subduct in the mantle along active converging margins, where the forces driving such a convergence can trigger large earthquakes. However, these subduction zones often deform without producing earthquakes, but through slow deformations called slow slip events (SSE). The Hikurangi Margin (HM) of New Zealand is a well‐studied subduction zone, producing both earthquakes and SSEs. The northern HM exhibits more frequent and shallower SSEs than the southern margin. Understanding what controls such differences can help improve the general understanding of subduction zone mechanics and earthquakes. One of the hypotheses is that the differences between the deformation of the northern and southern HM are controlled by the pressure of fluids at depth. We tested the elastic and fluid‐transport properties of four samples from the northern HM and found that the overriding plate, if not fractured, would be impermeable to fluids. We also tested a fractured sample and observed efficient healing that resets the initial permeability. We conclude that fracturing the overriding plate is fundamental to draining the fluids carried at depth by the subducting plate, and SSEs may create new pathways for fluids to escape to the seafloor. Key Points: We studied elastic properties, plastic deformation, and permeability of northern Hikurangi margin rocksWe provide a permeability‐porosity relationship for accretionary prism mudrocksPermeability healing in the Hikurangi accretionary prism rocks provides a mechanism justifying slow‐slip event cyclicity [ABSTRACT FROM AUTHOR]

Due to the complex nature of the pore system and the diversity of pore types, carbonate rocks pose a challenge in terms of their spatial characterization. Unlike sandstones, permeability in carbonates is often not correlated conclusively with porosity. A methodology for preliminary qualitative spatial characterization of reservoirs in carbonate rocks is presented in this article, with a focus on interparametric relationships. It endeavors to apply this methodology to a reservoir situated within the Main Dolomite formation in the Polish Lowlands. Fundamental analyses rely on data plotted within rock physics templates (RPT), specifically, cross-plots of acoustic impedance as a function of the product of compressional and shear wave velocities in well log profiles. The analysis of interparametric relationships was conducted on well log profiles and subsequently integrated with seismic data using neural network techniques. Areas with the greatest potential for hydrocarbon accumulation and areas potentially exhibiting enhanced reservoir properties were identified based on the outcomes of the well log profile analysis and parametric models. The qualitative assessment of the reservoir, rooted in interparametric dependencies encompassing lithofacies characteristics and elastic and petrophysical parameters, together with reservoir fluid saturation, forms the basis for further, more detailed reservoir analysis, potentially focusing on fracture modeling. [ABSTRACT FROM AUTHOR]

Reservoir characterization entails mapping properties such as lithology, fluid type, porosity and permeability, to describe reservoir quality and identify areas for the location of new wells for optimum production. In this study, we test the reliability of rock-physics modelling and model-based post-stack seismic inversion for characterizing reservoir rocks located within the 'Rhoda' field, onshore Niger Delta Basin, Nigeria. The aim is to accurately discriminate lithology and estimate reservoir properties for accurate prediction of new prospective areas within the field of interest. Unlike some conventional inversion and geomodelling algorithms, which are probabilistic, model-based post-stack seismic inversion is favoured for its sensitivity in resolving thin-bed tuning for increased stratigraphic resolution and reservoir property prediction. More so, it gives satisfactory results, even with limited well control and fair to poor seismic quality, as will be shown in this study. On the basis of gamma-ray and resistivity log signatures, two reservoir sands, dubbed D6000 and D7000, were identified in the field of study. Along the eastern direction, well correlation revealed a significant net sand reduction. Within the reservoirs of interest, petrophysical parameters such as water saturation (Sw), porosity (Ø), and shale volume (Vsh) were evaluated. With high Ø and low Sw and Vsh values, these reservoirs were classified as good quality reservoirs. Crossplots of well-log properties such as density vs acoustic impedance, velocity ratio vs acoustic impedance, gamma-ray vs density, and gamma-ray vs acoustic impedance showed lithologies and pore fluids such as hydrocarbon sand, brine-sand, and shale. The model-based post-stack seismic inversion results revealed a lateral distribution of hydrocarbon and brine sands characterized by low and moderate acoustic impedance values, respectively. The low values of acoustic impedance slice and seismic horizon attributes (instantaneous phase and frequency) identified away from the drilled locations imply the presence of hydrocarbon-charged sands, which are potential prospects for future exploitation. This study therefore, shows the effectiveness of rockphysics-based modelling and model-based post-stack seismic inversion in the characterization of reservoir sands within the Niger Delta Basin and can be applied in other provinces around the world. [ABSTRACT FROM AUTHOR]

Heavy oil has high density and viscosity, and exhibits viscoelasticity. Gassmann's theory is not suitable for materials saturated with viscoelastic fluids. Directly applying such model leads to unreliable results for seismic inversion of heavy oil reservoir. To describe the viscoelastic behavior of heavy oil, we modeled the elastic properties of heavy oil with varying viscosity and frequency using the Cole-Cole-Maxwell (CCM) model. Then, we used a CCoherent Potential Approximation (CPA) instead of the Gassmann equations to account for the fluid effect, by extending the single-phase fluid condition to two-phase fluid (heavy oil and water) condition, so that partial saturation of heavy oil can be considered. This rock physics model establishes the relationship between the elastic modulus of reservoir rock and viscosity, frequency and saturation. The viscosity of the heavy oil and the elastic moduli and porosity of typical reservoir rock samples were measured in laboratory, which were used for calibration of the rock physics model. The well-calibrated frequency-variant CPA model was applied to the prediction of the P- and S-wave velocities in the seismic frequency range (1–100 Hz) and the inversion of petrophysical parameters for a heavy oil reservoir. The pre-stack inversion results of elastic parameters are improved compared with those results using the CPA model in the sonic logging frequency (∼10 kHz), or conventional rock physics model such as the Xu-Payne model. In addition, the inversion of the porosity of the reservoir was conducted with the simulated annealing method, and the result fits reasonably well with the logging curve and depicts the location of the heavy oil reservoir on the time slice. The application of the laboratory-calibrated CPA model provides better results with the velocity dispersion correction, suggesting the important role of accurate frequency dependent rock physics models in the seismic prediction of heavy oil reservoirs. [ABSTRACT FROM AUTHOR]