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The complex pore structure of carbonate reservoirs hinders the correlation between porosity and permeability. In view of the sedimentation, diagenesis, testing, and production characteristics of carbonate reservoirs in the study area, combined with the current trends and advances in well log interpretation techniques for carbonate reservoirs, a log interpretation technology route of "geological information constraint þ deep learning" was developed. The principal component analysis (PCA) was employed to establish lithology identification criteria with an accuracy of 91%. The Bayesian stepwise discriminant method was used to construct a sedimentary microfacies identification method with an accuracy of 90.5%. Based on production data, the main lithologies and sedimentary microfacies of effective reservoirs were determined, and 10 petrophysical facies with effective reservoir characteristics were identified. Constrained by petrophysical facies, the mean interpretation error of porosity compared to core analysis results is 2.7%, and the ratio of interpreted permeability to core analysis is within one order of magnitude, averaging 3.6. The research results demonstrate that deep learning algorithms can uncover the correlation in carbonate reservoir well logging data. Integrating geological and production data and selecting appropriate machine learning algorithms can significantly improve the accuracy of well log interpretation for carbonate reservoirs. [ABSTRACT FROM AUTHOR]

Interpreting reservoir properties through log data and logging responses in complex strata is critical for efficient petroleum exploitation, particularly for metamorphic rocks. However, the unsatisfactory accuracy of such interpretations in complex reservoirs has hindered their widespread application, resulting in severe inconvenience. In this study, we proposed a multi-mineral model based on the least-square method and an optimal principle to interpret the logging responses and petrophysical properties of complex hydrocarbon reservoirs. We began by selecting the main minerals based on a comprehensive analysis of log data, X-ray diffraction, petrographic thin sections and scanning electron microscopy (SEM) for three wells in the Bozhong 19-6 structural zone. In combination of the physical properties of these minerals with logging responses, we constructed the multi-mineral model, which can predict the log curves, petrophysical properties and mineral profile. The predicted and measured log data are evaluated using a weighted average error, which shows that the multi-mineral model has satisfactory prediction performance with errors below 11% in most intervals. Finally, we apply the model to a new well "x" in the Bozhong 19-6 structural zone, and the predicted logging responses match well with measured data with the weighted average error below 11.8% for most intervals. Moreover, the lithology is dominated by plagioclase, K-feldspar, and quartz as shown by the mineral profile, which correlates with the lithology of the Archean metamorphic rocks in this region. It is concluded that the multi-mineral model presented in this study provides reasonable methods for interpreting log data in complex metamorphic hydrocarbon reservoirs and could assist in efficient development in the future. [ABSTRACT FROM AUTHOR]

This research uses both three-dimensional (3D) modeling and geologic well control to piece back together the architectural parts of the Late Cretaceous formations. The goal is to figure out the sizes, directions, locations, and controls of the layers of the fluvial sandstone reservoirs. Sequence stratigraphy is essential for 3D reservoir modeling and petroleum geology understanding in the Bahga oilfield. The purpose of this work is to create a static model that shows the layers and facies distribution in the reservoir interval. We will use data from nine well logs and 22 seismic lines calibrated by the Abu Roash G Member reservoir core intervals to accomplish this. The petrophysical study discovered three parts in the Abu Roash G Member reservoir rock: channel fill that is affected by tides, channel fill that is dominated by tides (intertidal sands), and channel top with lenticular bedded sandstone. The model's findings point to the existence of an NNW-oriented sand body, which could be a prime location to produce hydrocarbons. The original oil in place (OOIP) is about 3,438,279 Stock Tank Barrels (STB), and the oil reserve reaches up to 1,031,484 (STB). Sequence stratigraphic analysis using seismic and well log information (SB) reveals that the Upper Cretaceous AR/G reservoir of the Bahga field is characterized by third- and fourth-order stratigraphic sequences, which are constrained by three Maximum Flooding Surfaces (MFS) and two Sequence Boundaries. The integration of the derived geological model and sequence stratigraphic results can lower future extraction risk by identifying the locations and trends of the geologic facies with the necessary petrophysical properties for the hydrocarbon accumulations. [ABSTRACT FROM AUTHOR]

Knowledge of the heterogeneity of aquifers caused by sedimentary processes is essential for preferential flow path and flow time estimations due to the spreading of contaminants and ground water protection. Spectral Induced Polarization (SIP) method is a useful geophysical method that can be used to predict hydraulic properties from surface measurements, as there is a close connection between electrical and hydraulic parameters of rocks. Thus, the influence of aquifer heterogeneities such as sedimentary structures on the relationship between SIP parameters and hydraulic conductivity has been subject of some studies and is still an area of interest. In this paper we present the results of laboratory measurements on defined heterogeneous sand samples with the aim to improve the understanding of that connection. More specifically we investigated the dependence of hydraulic conductivity (K ), as well as several SIP parameters like quadrature conductivity ( σ ′ ′ ), in-phase conductivity ( σ ′ ), phase shift (φ ) and chargeability spectra ( m (τ) ), which were calculated by Debye decomposition, on the composition of samples. For the laboratory experiments a measurement cell was designed to carry out hydraulic flow experiments and 4-electrodes SIP measurements on samples in the decimeter scale. The samples consisted of two different sands with different grain size distributions. The two sands were combined in varying volume shares and geometries as well as in parallel and serial orientation relative to hydraulic and electrical current flow. The experimental results show that the SIP parameters and K are clearly dependent on the volume share of the sand components. In terms of preferential flow paths, known correlations to hydraulic conductivity could be reproduced, however the SIP parameters showed no dependency on the orientation of hydraulic heterogeneities. The results indicate that in samples, where the porosity and thus also the electrical conductivity amplitude are approximately homogeneous and only the grain surface area and hydraulic conductivity vary, the mean electrical parameters determined from the SIP data do not provide any information for recognising preferential flow within the scope of the measurement accuracy. [ABSTRACT FROM AUTHOR]

The Upper Paleozoic tight sandstone reservoirs on the eastern margin of the Ordos Basin exhibit strong heterogeneity and complex pore structures, leading to poor correlation between porosity and permeability and insufficient accuracy in permeability calculations to meet the requirements of reservoir fine evaluation. Therefore, a new method for high-precision permeability calculation based on flow zone index (FZI) reservoir classification is proposed. This method determines the number of reservoir classifications based on the characteristics of the FZI normal probability distribution plot and establishes FZI division criteria for reservoir types. Classified reservoirs exhibit similar flow characteristics, significantly improving the correlation between permeability and porosity. Based on nuclear magnetic resonance (NMR) combined with mercury injection capillary pressure (MICP) experiments, a modeling method for calculating the flow zone index based on the geometric mean of NMR T2 is proposed. This method realizes continuous calculation of FZI based on NMR logging, reservoir classification, and permeability for the entire wellbore, thereby constructing a new permeability prediction method for tight sandstone reservoirs based on NMR logging and FZI classification. Actual application results demonstrate that the permeability calculated using NMR logging is in high agreement with the permeability analyzed from core data, with an average relative error of 45.8%, proving the effectiveness of the proposed method in this study. [ABSTRACT FROM AUTHOR]

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Petrophysical and Geomechanical properties of rocks are important parameters in the design of engineering works and classification of rocks for engineering purposes. Recent studies indicate that geophysical methods, especially seismic and electrical, are able to estimate mechanical parameters and recognize spatial variations. In this research, to develop a predictive model for the uniaxial compressive strength (UCS), special electrodes were installed on the saturated core samples and simultaneously, the uniaxial compressive strength test and electric current flowing through the samples was done and variation of electrical resistivity during loading was measured in the laboratory. The results indicated that the structure and texture of rock had an important effect on the resistivity behavior during a mechanical loading. In this study, thirty core samples from the Fault breccias and Bimrocks (Block-in-matrix-rocks), were collected from different locations of Sabzkouh tunnel route in Chahar Mahal and Bakhtiari Provence. Regression analysis showed that there were generally strong correlations between the UCS and Resistivity in the samples having volumetric block proportion (VBP) of 25–75%. Multiple regression equations were derived for the prediction of UCS based on the resistivity and VBP values. The coefficient of determination (R2) and the root mean square error (RMSE) and the geometric mean error ratio (GMER) indices were calculated as 89.13%, 8.683 and 0.911, respectively, to characterize the prediction performance of the MLR model. The statistical test showed that the MLR model was valid and acceptable for predicting UCS. [ABSTRACT FROM AUTHOR]

This study aims to predict Yamama layers formation permeability of five wells: N1, N2, N3, N4, and N5, each containing Yamama, Yamama B and Yamama C layers. The permeability was calculated through two methods, namely the basic analysis and well-log techniques. The basic analysis method was conducted in the laboratory using a PERL-200 device. The results obtained using this method were more accurate as they matched the well-log results. Employing Matlab software, a neural network predicted permeability for 14 layers of 5 wells, with the second and fifth wells having only two layers. By constructing a 13-layer neural network, an appropriate network configuration can be achieved to discover the relationship between the input and output and produce a matching target result. [ABSTRACT FROM AUTHOR]

Accurately estimating the petrophysical properties of heterogeneous carbonate rocks across various scales poses significant challenges, particularly within the context of water and hydrocarbon reservoir studies. Digital rock analysis techniques, such as X‐ray computed microtomography and synchrotron‐light‐based imaging, are increasingly employed to study the complex pore structure of carbonate rocks. However, several technical limitations remain, notably the need to balance the volume of interest with the maximum achievable resolution, which is influenced by geometric properties of the source–detector distance in each apparatus. Typically, higher resolutions necessitate smaller sample volumes, leading to a portion of the pore structure (the sub‐resolution or unresolved porosity), that remain undetected. In this study, X‐ray microtomography is used to infer the fluid flow properties of a carbonate rock sample having a substantial fraction of porosity below the imaging resolution. The existence of unresolved porosity is verified by comparisons with nuclear magnetic resonance (NMR) data. We introduce a methodology for modeling the sub‐resolution pore structure within images by accounting for unresolved pore bodies and pore throats derived from a predetermined distribution of pore throat radii. The process identifies preferential pathways between visible pores using the shortest distance and establishes connections between these pores by allocating pore bodies and throats along these paths, while ensuring compatibility with the NMR measurements. Single‐phase flow simulations are conducted on the full volume of a selected heterogeneous rock sample by using the developed pore network model. Results are then compared with petrophysical data obtained from laboratory measurements. Core Ideas: Using digital rock analysis, we generated and reconnected sub‐resolution pores of a carbonate rock sample.A workflow is presented to allow the reconnection of detectable and sub‐resolution pores.We compared simulated absolute permeabilities of different pore networks with laboratory measurements.Digital rocks generated with a pore network model can serve as a complementary tool for studying fluid flow patterns. [ABSTRACT FROM AUTHOR]

Increased demand for decarbonization and renewable energy has led to increasing interest in engineered subsurface storage systems for large-scale carbon reduction and energy storage. In these applications, a working fluid (CO2, H2, air, etc.) is injected into a deep formation for permanent sequestration or seasonal energy storage. The heterogeneous nature of the porous formation and the fluid–rock interactions introduce complexity and uncertainty in the fate of the injected component and host formations in these applications. Interactions between the working gas, native brine, and formation mineralogy must be adequately assessed to evaluate the efficiency, risk, and viability of a particular storage site and operational regime. This study reviews the current state of knowledge about coupled geochemical–geomechanical impacts in geologic carbon sequestration (GCS), underground hydrogen storage (UHS), and compressed air energy storage (CAES) systems involving the injection of CO2, H2, and air. Specific review topics include (1) existing injection induced geochemical reactions in these systems; (2) the impact of these reactions on the porosity and permeability of host formation; (3) the impact of these reactions on the mechanical properties of host formation; and (4) the investigation of geochemical-geomechanical process in pilot scale GCS. This study helps to facilitate an understanding of the potential geochemical–geomechanical risks involved in different subsurface energy storage systems and highlights future research needs. [ABSTRACT FROM AUTHOR]

This study focuses on the comprehensive reservoir characterization of the 'Kukih' Field within the onshore northeastern Niger Delta region, Nigeria. The absence of its detailed description with delineated reservoir properties, lateral continuity, and their use to identify potential reservoir quality and heterogeneity necessitated this study. Integrating well log and 3D seismic data, the investigation aims to elucidate reservoir properties, lithofacies, and depositional environments to unravel hydrocarbon potential. The geological setting, encompassing the Agbada Formation of Early and Middle Miocene age, is scrutinized through detailed geologic analysis. Petrophysical evaluation of four well logs (Kukih-1, Kukih-2, Kukih-3, and Kukih-4) facilitated the determination of key parameters such as shale volume, effective porosity, and water saturation. Seismic interpretation further enriched the structural characterization of the field. Results showcase three predominant reservoir sands (A, B, and C) with distinct lithofacies and thickness variations. Effective porosity ranges from Fair to Excellent, with permeability exhibiting high values for hydrocarbon reservoir potential. Water saturation trends, lithofacies distributions, and structural features were illuminated through iso-parametric maps and seismic analyses. Depositional environments were inferred through facies analysis, revealing the presence of funnel-, cylinder-, and bell-shaped successions that hint at intricate marine sedimentary processes. Challenges owing to limited core data were acknowledged, and the integration of methodologies emerged as a pivotal strategy for enhanced reservoir understanding. This study underscores the 'Kukih' Field's hydrocarbon potential, accentuating the significance of multidisciplinary approaches in deciphering complex reservoir systems. In light of the petrophysical analysis derived from the well logs and the identification of structural highs through the structural maps, this study recommends the drilling of unexplored zones exhibiting promising structural characteristics. [ABSTRACT FROM AUTHOR]

Characteristics of stress‐dependent properties of rocks are commonly described by empirical laws. It is crucial to establish a universal law that connects rock properties with stress. The present study focuses on exploring the correlations among permeability, porosity, and compressibility observed in experiments. To achieve this, we propose a novel finite strain‐based dual‐component (FS‐DC) model, grounded in the finite strain theory within the framework of continuum mechanics. The FS‐DC model decomposes the original problem into the rock matrix and micro‐pores/cracks components. The deformation gradient tensor is utilized to derive the constitutive relations. One of the novelties is that the stress‐dependent variables are calculated in the current configuration, in contrast to the reference configuration used in small deformation theory. The model has only a few number of parameters, each with specific physical interpretations. It can be reduced to existing models with appropriate simplifications. Then, model performance is examined against experimental data, including permeability, porosity, compressibility, volumetric strain and specific storage. It proves that the variations of these properties are effectively described by the proposed model. Further analysis reveals the effect of pores/cracks parameters. The validity of the FS‐DC model is examined across a broad range of pressures. The results show that rock properties at high confining pressures (>$>$300 MPa) differ from those observed under relatively low pressures (<$<$200 MPa). This disparity can be attributed to inelastic behaviors of micro‐structure, wherein the rock skeleton undergoes permanent deformation and breakage. [ABSTRACT FROM AUTHOR]

Unconsolidated sand reservoirs containing heavy oil play a significant role in hydrocarbon resources, characterized by high porosity and permeability alongside abundant movable fines. During production, these fines can detach and migrate with the reservoir fluids, causing pore plugging and reduced productivity. Visualizing and quantitatively evaluating the evolution of pore structure caused by fines migration under various influencing factors at the microscale is fundamental for devising effective prevention and mitigation measures. This study employs on-line NMR experiments and CFD-DEM simulations to investigate fines migration processes and their effects on physical properties and pore structure at the pore scale. Results indicate that fines migration initiates the formation of a preferential network of migration pathways. The evolution of pore structure demonstrates zonal characteristics along the flow direction, with fines plugging and residual accumulation primarily occurring in the middle/rear section of the core. As the core's skeleton porosity decreases, fines plugging intensifies; however, at high injection velocity, new dominant flow channels may emerge, leading to a transition from a single-peak to a double-peak T2 spectrum. Below the critical velocity (0.5-1 mL/min), an increase in flow velocity exacerbates severe fines plugging. Conversely, above the critical velocity, an increase in flow velocity results in a more pronounced enhancement of permeability. [ABSTRACT FROM AUTHOR]

Herein, we have synthesised cobalt (Co) and copper (Cu) co‐doped Ni‐ferrite Ni1‐xCoxFe2‐yCuyO4 nanocrystals (NCs) via the facile micro‐emulsion method. The materials were analysed for various physio‐chemical characterizations to investigate the co‐doping (Co and Cu) effects on magnetic, structural, electrical, photo‐catalytic properties. The structural analysis via Fourier Transform Infrared spectroscopy (FTIR) and X‐rays diffraction (XRD) showed the successful fabrication of Co and Cu co‐doped materials with cubic spinel geometry having a single phase, the crystallite size was observed in 15 to 24 nm range. The electrical response measured using current‐voltage (I–V) analysis showed good electrical features, the electrical resistivity declined from 6.85×107 Ohm.cm for un‐doped materials to 0.04×107 Ohm.cm for co‐doped materials, which was accredited due to the synergistic effects of Co and Cu metal cations in co‐doped Ni‐based ferrite structures. Magnetic investigation using VSM analysis showed increased saturation magnetization (Ms 31.32 to 50.75 emu/g) and coercivity (218.76 to 406.82 Oe) because of the higher magnetic responses of Co2+ions in the co‐doped spinel ferrite NCs. BET surface‐area analysis showed good porosity for co‐doped materials with an increased surface area of 52 to 104 m2/g on co‐doping. The Tauc's plot described the decline of band‐gap energies value (Egs) (1.99 eV) in co‐doped (x=y=0.56) materials as compared to (2.16 eV) of the un‐doped NiFe2O4 materials, which is due to more electrical responses of Co and Cu co‐dopant cations that possess higher energy levels, which can stabilize the charge carrier's species. Furthermore, the photo‐degradation using solar light showed good removal of crystal violet (CV) dye, which was almost 94.14 % by co‐doped material; however, by un‐doped material, it was 38.044 %. The scavenger experiment shows that the (OH⋅) hydroxyl radicals and (e−/h+) species play a prime role in the degradation of CV dye. Recycling and recoverability tests for five cycles' exhibited outstanding stability of the photocatalyst with only 1.7 % losses in activity. Overall, our results showed that co‐doped Ni1‐xCoxFe2‐yCuyO4 NCs materials exhibited enhancement in the magnetic, electrical, photo‐catalytic properties and a decline in band‐gap energy values as compared to un‐doped NiFe2O4, which might have potential use in magnetic and electrical devices as well as solar‐driven photo‐catalyst materials for the remediation of environmental pollution. [ABSTRACT FROM AUTHOR]

The fractures network generated during the excavation of underground research facilities can induce stress redistribution and alteration of flow and transport properties, becoming preferential paths for releasing radionuclides into the host rock. Nevertheless, in the long term, the fracture can be sealed through the resaturation of water coming from the rock as a function of its self-sealing potential. Despite the large number of experimental studies that have proven the self-sealing capacity of clay rocks, very few attempts have been made to describe and predict the phenomenon numerically. This may be due to the difficulty of measuring the initial hydro-mechanical conditions. Besides, samples artificially fractured in the laboratory can be disturbed by the preparation process itself, which can alter the hydro-mechanical state. This paper addresses that issue by bridging the gap between experiments and numerical modeling. Representative experimental tests performed on Callovo–Oxfordian Claystone (COx) are used to offer a hydro-mechanical fracture law taking into account the self-sealing capacity of the material. Implementing such a model in a finite element code allows its validation through comparison with laboratory tests. Furthermore, the role of the initial fracture size and the evolution of water permeability during the wetting/drying process is investigated. Due to its transmissivity, injected water can penetrate the rock, initially reaching the damaged zone around the fracture before spreading through the entire sample. This progression is accounted in the constitutive equation and represented numerically. Nevertheless, a larger initial crack leads to reduced recovery rates. These results match the experiments, offering a valuable perspective in the modeling of self-sealing in in situ conditions. [ABSTRACT FROM AUTHOR]

In petrophysics, physical rock properties are typically established through laboratory measurements of individual samples. These measurements predominantly relate to the specific sample and can be challenging to associate with the rock as a whole since the physical attributes are heavily reliant on the microstructure, which can vary significantly in different areas. Thus, the obtained values have limited applicability to the entirety of the original rock mass. To examine the dependence of petrophysical measurements based on the variable microstructure, we generate sets of random 2-D microstructure representations for a sample, taking into account macroscopic parameters such as porosity and mean grain size. For each microstructure produced, we assess the electrical conductivity and evaluate how it is dependent on the microstructure's variability. The developed workflow including microstructure modelling, finite-element simulation of electrical conductivity as well as statistical and petrophysical evaluation of the results is presented. We show that the methodology can adequately mimic the physical behaviour of real rocks, showing consistent emulation of the dependence of electrical conductivity on connected porosity according to Archie's law across different types of pore space (microfracture, intergranular and vuggy, oomoldic pore space). Furthermore, properties such as the internal surface area and its fractal dimension as well as the electrical tortuosity are accessible for the random microstructures and show reasonable behaviour. Finally, the possibilities, challenges and meshing strategies for extending the methodology to 3-D microstructures are discussed. [ABSTRACT FROM AUTHOR]

Tick Hill gold deposit is a unique gold mineralisation style in the Mary Kathleen Fold Belt in the Mount Isa Inlier. The gold at Tick Hill is generally pure without silver and was formed during two discrete metamorphic-deformation events (D1 and D3). Early gold was observed as inclusions or coarse grains hosted within D1 peak-metamorphic diopside, scapolite and hornblende from the garnet–biotite–hornblende (tschemakite)–plagioclase (andesine)–quartz assemblage. Late gold is closely associated with bismuth selenide, chlorite, albite, sericite and K-feldspar, and formed during D3. The syn-D1 garnet–plagioclase–hornblende–quartz–biotite assemblage was used to constrain the pressure and temperature (P–T) conditions of metamorphism and mineralisation using the garnet–plagioclase–hornblende–quartz barometer and the hornblende–plagioclase, garnet–biotite and garnet–hornblende thermometers. The results show that peak metamorphism at Tick Hill reached P–T conditions of 6.0–7.6 kbar and 720–760 °C. These P–T conditions together with gneissic and migmatisation textures recorded in different rock types at the Tick Hill area indicate that the peak metamorphism preserved in the area occurred at the amphibolite–granulite facies, compared with the amphibolite facies at the southern Mary Kathleen and Eastern Fold Belt. The D3 chlorite, which formed during stage 2 to stage 4 mineralisation events, displays a wide range of compositions reflecting a gradual retrograde temperature change from ∼380 °C to ∼130 °C. The pressures during D3 could not be reliably determined, but the presence of various Bi-selenides suggests that towards the waning stages of D3, the rocks may have been exhumed to a pressure less than 1 kbar. The 1790–1770 Ma D1 peak metamorphism at Tick Hill reached 6–7.6 kbar and 720–760 °C. The 1525–1520 Ma D3 hydrothermal mineralisation at Tick Hill Deposit occurred at temperatures between ∼380 °C and ∼130 °C. The main D3 gold accumulation episodes at Tick Hill occurred at temperatures ranging from ∼380 to 160 °C. [ABSTRACT FROM AUTHOR]

Flow units (FU) rock typing is a common technique for characterizing reservoir flow behavior, producing reliable porosity and permeability estimation even in complex geological settings. However, the lateral extrapolation of FU away from the well into the whole reservoir grid is commonly a difficult task and using the seismic data as constraints is rarely a subject of study. This paper proposes a workflow to generate numerous possible 3D volumes of flow units, porosity and permeability below the seismic resolution limit, respecting the available seismic data at larger scales. The methodology is used in the Mero Field, a Brazilian presalt carbonate reservoir located in the Santos Basin, who presents a complex and heterogenic geological setting with different sedimentological processes and diagenetic history. We generated metric flow units using the conventional core analysis and transposed to the well log data. Then, given a Markov chain Monte Carlo algorithm, the seismic data and the well log statistics, we simulated acoustic impedance, decametric flow units (DFU), metric flow units (MFU), porosity and permeability volumes in the metric scale. The aim is to estimate a minimum amount of MFU able to calculate realistic scenarios porosity and permeability scenarios, without losing the seismic lateral control. In other words, every porosity and permeability volume simulated produces a synthetic seismic that match the real seismic of the area, even in the metric scale. The achieved 3D results represent a high-resolution fluid flow reservoir modelling considering the lateral control of the seismic during the process and can be directly incorporated in the dynamic characterization workflow. [ABSTRACT FROM AUTHOR]

Research on reservoir rock stress sensitivity has traditionally focused on unary granular structures, neglecting the binary nature of real reservoirs, especially tight reservoirs. Understanding the stresssensitive behavior and mathematical characterization of binary granular media remains a challenging task. In this study, we conducted online-NMR experiments to investigate the permeability and porosity evolution as well as stress-sensitive control mechanisms in tight sandy conglomerate samples. The results revealed stress sensitivity coefficients between 0.042 and 0.098 and permeability damage rates ranging from 65.6% to 90.9%, with an average pore compression coefficient of 0.0168e0.0208 MPa-1. Pore-scale compression occurred in three stages: filling, compression, and compaction, with matrix pores playing a dominant role in pore compression. The stress sensitivity of binary granular media was found to be influenced by the support structure and particle properties. High stress sensitivity was associated with small fine particle size, high fines content, high uniformity coefficient of particle size, high plastic deformation, and low Young's modulus. Matrix-supported samples exhibited a high irreversible permeability damage rate (average = 74.2%) and stress sensitivity coefficients (average = 0.089), with pore spaces more slit-like. In contrast, grain-supported samples showed low stress sensitivity coefficients (average = 0.021) at high stress stages. Based on the experiments, we developed a mathematical model for stress sensitivity in binary granular media, considering binary granular properties and nested interactions using Hertz contact deformation and Poiseuille theory. By describing the change in activity content of fines under stress, we characterized the non-stationary state of compressive deformation in the binary granular structure and classified the reservoir into three categories. The model was applied for production prediction using actual data from the Mahu reservoir in China, showing that the energy retention rates of support-dominated, fill-dominated, and matrix-controlled reservoirs should be higher than 70.1%, 88%, and 90.2%, respectively. [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]

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]

Numerical simulation of nuclear magnetic resonance (NMR) can simulate experimental scenarios and quantify the impact of each factor on the physical characteristics. However, general simulation methods lack authentic pore structure information and fail to accurately model the complex geometry of rocks. High-resolution digital rock cores can effectively reflect pore structure. In this paper, a high-resolution digital core of Berea sandstone is taken as the research object, the pore parameters of the core (e.g., pore volume and surface-to-volume ratio) are quantified, and the 12 529 pores extracted from the three-dimensional digital core are statistically analyzed. Subsequently, the pores are classified based on their surface-to-volume ratio and volume. After the simulation parameters are calibrated by the experiments, NMR response of different water-saturated pores is simulated. Finally, the NMR response of the core with different oil saturation is simulated. We find that the distribution of pore quantity in terms of volume and surface area both follows a power function. There is a strong correlation between pore volume and surface area, especially for smaller pores. The T2 (transverse relaxation time) spectrum can generally reflect the volume distribution, but it may not accurately reflect the volume distribution when the pores are large. We also observe that the spectrum peak reflecting oil bulk relaxation is positioned to the left of the peak of the oil bulk relaxation due to the combined effects of surface relaxation of residual water and diffusion relaxation. These simulation results provide a physical basis for interpreting NMR measurements and can help identify fluids in reservoirs. [ABSTRACT FROM AUTHOR]

Spontaneous water imbibition into matrix blocks can be a significant oil recovery mechanism in fractured reservoirs. Many enhanced oil recovery methods, such as injection of modified salinity brine, are proposed for improving spontaneous imbibition efficacy. Many scaling equations are developed in the literature to predict spontaneous imbibition oil recovery. However, almost none of them included the impact of the diversity in ionic composition of injected and connate brines and the blending/interaction of a low salinity imbibing brine with a higher salinity connate brine. In this research, these two issues are included to propose new scaling equations for the scaling of spontaneous imbibition oil recovery by modified salinity imbibing brines. This study uses experimental data of the spontaneous imbibition of modified salinity brines into oil-saturated rock samples with different lithologies containing an irreducible high salinity connate brine. The collected tests from the literature were performed at high temperatures and on aged altered wettability cores. The results of 110 available spontaneous imbibition laboratory experiments (85, 12 and 13 tests on chalks, dolomites and sandstones, respectively) are gathered. This research initially shows the poor ability of three selected convenient scaling equations from the literature to scale imbibition recovery by modified salinity brine. Then, our newly proposed technique to find the scaling equation for spontaneous imbibition recovery by modified salinity brine, during the abovementioned conditions in limestones (Bassir et al. in J Pet Explor Prod Technol 13(1): 79–99, 2023. https://doi.org/10.1007/s13202-022-01537-7) is used in chalks, dolomites and sandstones to develop the three new scaling equations. Finally, a new general equation to scale imbibition recovery by modified salinity brine for all four lithologies is presented. Moreover, for each of the four datasets (chalk, dolomite, sandstone and all the four lithologies), the scaled data by the new equations is matched by two mathematical expressions based on the Aronofsky et al. model and the Fries and Dreyer model. These mathematical expressions can be used to develop transfer functions in reservoir simulators for a more accurate prediction of oil recovery by spontaneous imbibition of modified salinity brine in fractured reservoirs. [ABSTRACT FROM AUTHOR]

Kadanwari is a major gas-producing field in Pakistan's Lower Indus Basin (LIB), extensively explored for optimized production. However, the reservoir sands of the Lower Goru Formation (LGF), deposited in a complex river-dominated delta, bear severe variability and hinder accurate facies approximation for optimal production. Furthermore, the regionally extended NNW-SSE directed horst and graben structures significantly compartmentalized these reservoir facies. The main E-sand interval is analyzed for its geological properties, depositional environment, and distribution. The integration of various approaches, including seismic interpretation, attribute extraction, well-based facies modeling, and petrophysical evaluation, proved significant in evaluating the heterogeneous and tectonically influenced E-sands. The discontinuity attribute substantially highlighted the structural style and aided in analyzing the geometries of faults. The low values of the frequency attribute (< 10 Hz) signified the entrapped gas-bearing sands along the faulted zones. The high responses of instantaneous amplitude and sweetness profoundly illuminated the gas-significant deposits throughout the field in association with the well-identified gas-prone sand facies. The outcomes of the neutron-density crossplot depicted gas-bearing sands having low density (< 2.3 g/cc) and good porosity (12%) with the assessment of various cements. The facies modeling distinguished between clean and intermixed sand-shale reservoir zones. Petrophysical analysis revealed a net pay of 14 m within E-sand having gas saturation of about 68%. The adopted approach is robust and efficient, employing a limited data set for developing well-associated seismic responses for potential zone delineation within structural arrangements. The techniques can be optimistic about the LGF's complex potential sands demarcation throughout the Indus Basin. [ABSTRACT FROM AUTHOR]

Rates of seismicity in the Delaware Basin of Texas and New Mexico increased from 10 earthquakes per year of local magnitude (ML) 3.0 and above in 2017 to more than 185 in 2022, coincident with increasing oil and gas production and wastewater re‐injection into strata shallow or deeper than producing intervals. Events of large magnitude—up to ML 5.4 to‐date—occur on faults extending into formations above the basement that have received more than four billion barrels of injection. Here, we demonstrate the link between injection geology, pore pressure evolution, fault stability, and induced seismicity in this region. We find that the injection targets are largely dolomitized platform carbonates with low (<5 vol.%) matrix porosity and fracture‐enhanced permeability with inherent heterogeneity in flow properties. A comprehensive, three‐dimensional geological model populated with reservoir properties is used for fluid flow modeling, with global calibration supplemented by dynamic injectivity data. Pore pressure changes with deep injection are up to 5 MPa from 1983 to 2023, increasing the native pore pressure state by 10% locally. Modeling results show that earthquakes occurring at distances of up to 30 km from deep injection have experienced small (<0.1 MPa) pore pressure increases, indicating that the faults hosting these earthquakes are highly sensitive to changes in effective stress and have lower frictional stability than the 0.6 generally assumed. These results serve as a critical step in understanding the stress changes that induce earthquakes in one of the most seismically active and geologically complex basins in the US. Plain Language Summary: Earthquakes have become more frequent in areas with historically little seismicity and are coincident in space and time with an increase in oil and gas production and the re‐injection of wastewater. Larger‐magnitude earthquakes occur on deep faults and generally within the crystalline basement. They are likely caused by wastewater injection into carbonate rocks above the basement, causing changes in pressure and stress on nearby faults. Results from this modeling work show that deep fluid injection increases pressure by up to 10% near deep injection wells. Key Points: Injection of oil field wastewater into deep strata in the Delaware Basin causes pore pressure changes of up to 5 MPaEarthquakes occurring in crystalline basement are likely induced by pore pressure diffusion associated with regional deep injectionMany basement‐rooted faults hosting earthquakes are optimally oriented, sensitive, and slip with small pore pressure perturbations [ABSTRACT FROM AUTHOR]

The study of deep shale gas (>3500 m) has become a new research hotspot in the field of shale gas research in China. In this study, 16 representative deep shale samples were selected from different layers of the Wufeng–Longmaxi Formation in the Z-3 well in the western Chongqing area to conduct low-field nuclear magnetic resonance (NMR) tests, field-emission scanning electron microscopy (FE-SEM) observation, and fractal modeling. By comparing the differences in pore structure and their influencing factors in representative samples from different layers, the particularities of high-quality reservoirs have been revealed. The results show that the Z-3 well shales mainly develop micropores and mesopores, with pore sizes of 1 nm–200 nm. The fractal dimensions of bound fluid pores D1 (1.6895–2.3821) and fractal dimension of movable fluid pores D2 (2.9914–2.9996) were obtained from T2 spectra and linear fitting, and the pores were divided into three sections based on the NMR fractal characteristics. TOC content was one of the major factors affecting the gas content in the study area. The shale samples in the bottom S1l1-1 sub-layer with a higher TOC content have larger porosity and permeability, leading to enhanced homogeneity of the pore structure and favorable conditions for shale gas adsorption. A comparative understanding of the particularities of pore structure and influencing factors in high-quality reservoirs with higher gas content will provide the scientific basis for further exploration and exploitation of the Wufeng–Longmaxi Formation deep shale reservoirs in the western Chongqing area. [ABSTRACT FROM AUTHOR]

The estimation of permeability in carbonate formations remains one of the main challenges in reservoir engineering. Existing literature predominantly utilizes total porosity as the sole input for characterizing permeability. However, the recognition of other influential parameters and their corresponding correlations is deemed important for enhancing accuracy, particularly in heterogeneous tight and deep carbonate formations. Despite progress, a universal, accurate, and straightforward approach for achieving this goal is still lacking. In this study, the advanced heuristic algorithm known as gene expression programming (GEP) is employed to estimate absolute permeability. An all-inclusive database that includes permeability, formation resistivity factor, total porosity, moldic porosity, interparticle porosity, and non-fabric-selective dissolution (connected) porosity is compiled from existing literature. Initially, a sensitivity analysis is conducted to identify the key variables affecting permeability. Notably, the formation resistivity factor emerges as the most relevant variable on permeability prediction. Subsequently, the reliability of the database is assessed using Williams' plot to detect outliers. After excluding the outlier data and considering the detected influential variable on permeability, multiple realizations of GEP modeling strategies are constructed. As a result, four GEP-derived symbolic equations are proposed. Statistical measures and graphical analyses demonstrate that GEP Model-IV provides the most accurate estimations, with a root mean square error (RMSE) of 1.09, a determination coefficient (R2) of 0.72, and a mean absolute error (MAE) of 1.33. Furthermore, the accuracy of the proposed GEP Model-IV is verified by Williams' plot, covering approximately 97.32% of the databank. Finally, it is recognized that considering pore description parameters enhances the accuracy of permeability estimation, particularly in studies characterizing carbonate reservoirs, especially when dealing with tight and deep formations. [ABSTRACT FROM AUTHOR]

A very common hazard in Rwanda is represented by the instability of steep road cut slopes in lateritic soil. In its natural state, this material appears as a fine-grained weak and altered rock, generally in unsaturated conditions. Steep cut slopes made by this material could remain stable for a long time unless weathering weakens its mechanical behavior and heavy rainfall provokes a rapid landslide. This paper presents the results of an experimental investigation on the microstructural, petrophysical, and geotechnical properties of lateritic soil from a road cut slope located in Kabaya (Ngororero District—Rwanda), which was recently subjected to a landslide. The mechanical properties of the material are strictly related to the geological origin and history of the deposits, their formation environment, and weathering processes. These characteristics were revealed by peculiar microstructural features (micro-texture, porosity, and degree of alteration of original mineral paragenesis). The experimental investigations included identification and classification tests, direct shear tests on saturated samples, and swelling tests. This multidisciplinary approach provided insights into the relationship between geotechnical properties and the microstructural, petrophysical, and chemical characteristics of the altered rocks. This study showed how different levels of chemical alteration operated by weathering processes, in conjunction with brittle deformation related to the tectonic history, formed in the same site two shallow rock layers with similar macro-scale features and mechanical behaviors but markedly different microstructural and chemical properties. The innovative aspect of this research suggests an integrated multidisciplinary approach to considering microstructural aspects in addition to mechanical behavior in the slope stability analyses in lateritic soil. In particular, this study demonstrates the importance of such an approach since the failure mechanism is better explained if it is based on microstructural observations instead of considering the soil shear strength parameters only. This research helped to explain the formation of the landslide failure mechanism in a specific road cut slope, which could be assumed as representative of many other similar slopes subjected to landslides in Rwanda. [ABSTRACT FROM AUTHOR]

Summary: As the geoenergy sector moves toward more sustainable practices, an emerging field of research is the proposed utilization of cyclic hydraulic pressure pulses to safely and efficiently enhance productivity. We demonstrate how cyclic hydraulic pressure pulses can reduce hydraulic breakdown pressure in granite using newly developed experimental equipment, which applies pulsed square waves of fluid pressure to large bench-top samples, monitored with dynamic high-resolution fiber optic strain sensors. Our results show a significant reduction in breakdown pressure can be achieved by cyclic pulsed pumping, and we explore the role of mean pressure and cyclic amplitude. Our results offer new insight into cyclic well-stimulation treatments and show potential for reducing peak power consumption during geothermal exploitation.

The ferrimagnetic rare-earth-free Mn4N films are considered as a good candidate in spintronics due to its low saturation magnetization (MS) and high Néel temperature. Here, Mn4N films are directly deposited on flexible mica to investigate strain-related magnetic and electronic transport properties. The MS variation of 11.0 nm Mn4N film reaches 453% at tensile strain of radius of curvature (ROC) = 2 mm. Bending strains cannot affect anomalous Hall resistivity and magnetoresistance. However, the topological Hall resistivity of 147.0 nm Mn4N film increases by 58% at tensile strain of ROC = 5 mm due to frustrated exchange interactions. The flexible Mn4N films have great potential applications in flexible magnetic sensor and strain gauge due to strain modulated MS, resistance, and stable magnetoresistance. [ABSTRACT FROM AUTHOR]

Abstract Understanding water saturation levels in tight gas carbonate reservoirs is vital for optimizing hydrocarbon production and mitigating challenges such as reduced permeability due to water saturation (Sw) and pore throat blockages, given its critical role in managing capillary pressure in water drive mechanisms reservoirs. Traditional sediment characterization methods such as core analysis, are often costly, invasive, and lack comprehensive spatial information. In recent years, several classical machine learning models have been developed to address these shortcomings. Traditional machine learning methods utilized in reservoir characterization encounter various challenges, including the ability to capture intricate relationships, potential overfitting, and handling extensive, multi-dimensional datasets. Moreover, these methods often face difficulties in dealing with temporal dependencies and subtle patterns within geological formations, particularly evident in heterogeneous carbonate reservoirs. Consequently, despite technological advancements, enhancing the reliability, interpretability, and applicability of predictive models remains imperative for effectively characterizing tight gas carbonate reservoirs. This study employs a novel data-driven strategy to prediction of water saturation in tight gas reservoir powered by three recurrent neural network type deep/shallow learning algorithms—Gated Recurrent Unit (GRU), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Support Vector Machine (SVM), K-nearest neighbor (KNN) and Decision tree (DT)—customized to accurately forecast sequential sedimentary structure data. These models, optimized using Adam's optimizer algorithm, demonstrated impressive performance in predicting water saturation levels using conventional petrophysical data. Particularly, the GRU model stood out, achieving remarkable accuracy (an R-squared value of 0.9973) with minimal errors (RMSE of 0.0198) compared to LSTM, RNN, SVM, KNN and, DT algorithms, thus showcasing its proficiency in processing extensive datasets and effectively identifying patterns. By achieving unprecedented accuracy levels, this study not only enhances the understanding of sediment properties and fluid saturation dynamics but also offers practical implications for reservoir management and hydrocarbon exploration in complex geological settings. These insights pave the way for more reliable and efficient decision-making processes, thereby advancing the forefront of reservoir engineering and petroleum geoscience.

In current review, we consider the Russian and, mainly, international experience of the “digital core» technology, namely – the possibility of creating a numerical models of internal structure of the cores and multiphase flow at pore space scale. Moreover, our paper try to gives an answer on a key question for the industry: if digital core technology really allows effective to solve the problems of the oil and gas field, then why does it still not do this despite the abundance of scientific work in this area? In particular, the analysis presented in the review allows us to clarify the generally skeptical attitude to technology, as well as errors in R&D work that led to such an opinion within the oil and gas companies. In conclusion, we give a brief assessment of the development of technology in the near future.

Abstract The primary objective of this study is to identify and analyze the petrophysical properties of the newly investigated AEB_IIIG member reservoir in Meleiha West Deep (MWD) Field and to classify it into different rock types. Additionally, this research intends to develop mathematical equations that may be utilized to estimate permeability in uncored sections of the same well or in other wells where core samples are unavailable. The analysis focused on the pore hole records of ten wells that were drilled in MWD Field. The reservoir levels were identified, and their petrophysical parameters were evaluated using well logs and core data. We were able to recognize seven different types of rocks (petrophysical static rock type 1 (PSRT1) to PSRT7) using petrography data, the reservoir quality index (RQI), the flow zone index (FZI), R35, hydraulic flow units (HFUs), and stratigraphy modified Lorenz (SML) plots. The analysis of the petrophysical data shows that AEB_IIIG has unsteady net pay thicknesses over the area. It has a range of 8–25% shale volume, 12–17% effective porosity, and 72–92% hydrocarbon saturation. The RQI results show that psrt1, psrt2 and psrt3 have a good reservoir quality as indicated by high R35 and helium porosity, respectively. They contribute with more than 75% of the reservoir production. The equation derived for each rock type of AEB_IIIG reservoir can be employed to forecast the permeability value distribution inside the reservoir.

Understanding water saturation levels in tight gas carbonate reservoirs is vital for optimizing hydrocarbon production and mitigating challenges such as reduced permeability due to water saturation (Sw) and pore throat blockages, given its critical role in managing capillary pressure in water drive mechanisms reservoirs. Traditional sediment characterization methods such as core analysis, are often costly, invasive, and lack comprehensive spatial information. In recent years, several classical machine learning models have been developed to address these shortcomings. Traditional machine learning methods utilized in reservoir characterization encounter various challenges, including the ability to capture intricate relationships, potential overfitting, and handling extensive, multi-dimensional datasets. Moreover, these methods often face difficulties in dealing with temporal dependencies and subtle patterns within geological formations, particularly evident in heterogeneous carbonate reservoirs. Consequently, despite technological advancements, enhancing the reliability, interpretability, and applicability of predictive models remains imperative for effectively characterizing tight gas carbonate reservoirs. This study employs a novel data-driven strategy to prediction of water saturation in tight gas reservoir powered by three recurrent neural network type deep/shallow learning algorithms—Gated Recurrent Unit (GRU), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Support Vector Machine (SVM), K-nearest neighbor (KNN) and Decision tree (DT)—customized to accurately forecast sequential sedimentary structure data. These models, optimized using Adam's optimizer algorithm, demonstrated impressive performance in predicting water saturation levels using conventional petrophysical data. Particularly, the GRU model stood out, achieving remarkable accuracy (an R-squared value of 0.9973) with minimal errors (RMSE of 0.0198) compared to LSTM, RNN, SVM, KNN and, DT algorithms, thus showcasing its proficiency in processing extensive datasets and effectively identifying patterns. By achieving unprecedented accuracy levels, this study not only enhances the understanding of sediment properties and fluid saturation dynamics but also offers practical implications for reservoir management and hydrocarbon exploration in complex geological settings. These insights pave the way for more reliable and efficient decision-making processes, thereby advancing the forefront of reservoir engineering and petroleum geoscience. [ABSTRACT FROM AUTHOR]

Extralow-permeability reservoirs have emerged as a significant area of focus for CO2 geological sequestration due to their stable subterranean structure and expansive storage capacity, offering substantial potential in addressing global climate change. However, the full extent of CO2 geological sequestration potential within these extralow-permeability reservoirs remains largely unexplored. To address this gap, this paper utilizes the Shahejie Formation (Es1 member) of the Shuang 229 block in the Liaohe oilfield, Bohai Bay Basin, as a case study. This section is characterized by its abundant oil-gas reserves and serves as an exemplar for conducting experimental research on CO2 storage within extralow-permeability reservoirs. The results demonstrate that the reservoir lithology of the Es1 member is fine sandstone and siltstone, with high compositional and structural maturity. Moreover, the average porosity is 14.8%, the average permeability is 1.48 mD, and the coefficient of variation of the reservoir is approximately 0.5, which indicates a low- to extralow-permeability homogeneous reservoir. In addition, the overburden pressure is >2.0 MPa, the fault can withstand a maximum gas column height of >200 m, and the reservoir exhibits favorable overburden and fault sealing characteristics. Notably, stepwise increasing gas injection in the Shuang 229-36-62 well reveals that the injected liquid CO2 near the wellhead exhibits a relatively high density, close to 1.0 g/cm3, which gradually decreases to approximately 0.78 g/cm3 near a depth of 2000 m underground. The injected fluid changes into a supercritical state upon entering the formation, and the CO2 injection speed is optimal, at 0.08 HCPV/a. According to these findings, it is predicted that the highest burial CO2 volume via the injection of 1.5 HCPVs in the Wa 128 block area is 1.11 × 105 t/year, and the cumulative burial volume reaches approximately 2.16 × 106 t. This shows that the CO2 sequestration potential of extralow-permeability reservoirs is considerable, providing confidence for similar instances worldwide. [ABSTRACT FROM AUTHOR]

The present study investigates the influences of SiC incorporation on the microstructure and corrosion behavior of B4C–nSiC composites in molten FLiNaK salt at 800°C. The corrosion characteristics and mechanisms of B4C–nSiC composites in molten FLiNaK salt were thoroughly characterized and extensively discussed. The B4C–nSiC composites exhibited a more refined grain size and lowered apparent porosity as the SiC content increased. Additionally, the concentration of high‐angle grain boundaries (HAGBs) in B4C–nSiC composites increased as the SiC content increased. The incorporation of 10 wt.% SiC improved the corrosion resistance of B4C–nSiC composites against molten FLiNaK salt. However, the incorporation of excessive SiC (≥20 wt.%) did not improve the corrosion resistance. The best corrosion resistance of B4C–10% SiC ceramic composite was attributed, on the one hand, to its relatively low apparent porosity and the low concentration of HAGBs with high structural disorder. On the other hand, the selective corrosion of B4C in B4C–10% SiC ceramic composite rapidly formed a sufficiently thick and highly graphitized C‐rich layer on its surface during the initial stages of the corrosion test. The C‐rich layer maintained the integral structure of the ceramic and prevented subsequent corrosive medium from penetrating into the ceramic. [ABSTRACT FROM AUTHOR]

Carbon Capture and Storage (CCS) is a key element to achieving net‐zero energy challenge timely. CCS operations require the integration of geophysical data, such as seismic and electromagnetic surveys, numerical reservoir models and fluid flow simulations. However, the 10–100s m resolution of seismic imaging methods complicates the mapping of smaller scale rock heterogeneities, while borehole measurements commonly show large fluctuations at sub‐cm scales. In this study, we combine laboratory data, well‐logging, rock physics theories and a proof‐of‐concept time‐lapse seismic modeling to assess the effect of pore‐scale fluid distribution and petrophysical heterogeneities on the expected performance of whole‐reservoir CCS operations in deep saline aquifers, by analogy to the Aurora CCS site, North Sea. We monitored the elastic and electrical properties of three sandstone samples with slightly different physical and petrographic properties during carbon dioxide (CO2) flow‐through tests under equivalent in situ effective pressure. We inferred the CO2‐induced damage in the rocks from the variations of their hydromechanical properties. We found that the clay fraction, CO2‐clay chemical interactions, and porosity were the main factors affecting both the CO2 distribution in the samples and the hydromechanical response. We used seismic modeling of well‐log data and the laboratory results to estimate the reservoir‐scale time‐lapse seismic response to CO2 injection and to assess the effect of the rock heterogeneities in our interpretation. The results show that disregarding the effect of rock heterogeneities on the CO2‐brine fluids distribution can lead to significant misinterpretations of seismic monitoring surveys during CCS operations in terms of both CO2 quantification and distribution. Plain Language Summary: Excess of carbon dioxide (CO2) in the atmosphere is causing global warming. The most realistic long‐term and large‐scale mitigation technology is Carbon Capture (Utilization) and Storage (CC(U)S). The CO2 is captured from the main sources of emissions and injected into deep geological formation for its permanent disposal. Offshore saline aquifers formed by siliciclastic reservoir rocks (sandstones) appear as suitable emplacements due to large storage capacity, pore connectivity and low CO2‐fluid‐rock chemical reactivity. The main challenge for CCS is to ensure CO2 remains contained in the subsurface storage volume. Seismic and electromagnetic sources are the most widely used geophysical remote sensing tools in reservoir exploration, and in the last couple of decades also for CO2 plume monitoring. However, reservoir rocks are not homogeneous bodies, and heterogeneities can largely affect our geophysical interpretation of CCS reservoirs. In this contribution we assess how the geophysical responses of rock samples associated with their hydromechanical changes during CO2 injection might vary as a result of small differences in porosity, shale fraction and clay content between them. Key Points: Porosity, grain size and clay minerals affect carbon dioxide (CO2) distribution in sandstones differentlyCO2‐induced P‐wave attenuation varies inversely with the clay content4D seismic model shows large scale misinterpretations of CO2 quantification if disregarding reservoir heterogeneities [ABSTRACT FROM AUTHOR]

Seismic and electromagnetic explorations are two of the most successful geophysical applications for understanding the subsurface earth, and the joint interpretation of seismic and electromagnetic survey data can help to better characterize the rocks because they contain independent and complementary information about the rocks. However, the success of the joint interpretation depends on the understanding of the correlations between the elastic and electrical rock properties and their influencing factors. Confining pressure is an important geological parameter that has been found to give rise to linear elastic–electrical correlations in sandstones. However, it is still poorly known what controls the slopes of the pressure-dependent linear correlations, even though slope is one of the most important parameters determining the linear correlation. We make artificial sandstones with controlled porosity and permeability, respectively, and measure their pressure-dependent elastic (electrical resistivity) and electrical (P -wave velocity) properties simultaneously, as well as porosity. We show that the slopes of the measured electrical resistivity versus P -wave velocity as an implicit function of confining pressure correlate positively with the compliant porosity in all the samples. The results not only reveal the petrophysical parameter that controls the slopes of the pressure-dependent linear elastic–electrical correlations in sandstones, but also provide a basis for the discrimination of the slope-controlling parameter from the simultaneously measured elastic and electrical properties. [ABSTRACT FROM AUTHOR]

The aim of this study was the synthesis of bimetallic nanoparticles based on Fe2O3/TiO2 and its use in the poly(lactic acid) (PLA) films as an oxygen scavenger in extra virgin olive oil (EVOO) packaging. Bimetallic nanocomposites were prepared by two different precipitation methods (precipitation with ammonia and sodium hydroxide). The characteristics of bimetallic nanoparticles precipitated with sodium hydroxide (Na‐Ti0.01Fe0.048O0.08) and bimetallic nanoparticles precipitated with ammonia (NH‐Ti0.01Fe0.022O0.09) were compared. Relative amounts of elements in bimetallic nanocomposites and their morphological characteristics were determined using field emission scanning electron microscopy coupled with energy‐dispersive X‐ray spectrometer. Porosity volume and surface area of bimetallic nanoparticles were calculated using adsorption–desorption isotherms and the Brunauer–Emmett–Teller method. The formation/characterization of bimetallic nanoparticles and their location in the matrix of PLA‐based nanocomposite film was studied using X‐ray diffraction and Fourier transform infrared. In nanocomposite films based on PLA, bimetallic nanoparticles lead to better oxidative stability (peroxide value, p‐anisidine index, K232, and K270) of the EVOO and oxygen scavenging during storage compared to free nanoparticles. Mechanical properties of nanocomposite films were improved due to bimetallic nanoparticles, which were better for Na‐Ti0.01Fe0.048O0.08. In vitro release modeling of the bimetallic nanoparticles in EVOO proved that Fickian diffusion is the dominant mechanism, and the Peleg model was the best description of the release behavior of nanoparticles. [ABSTRACT FROM AUTHOR]

Large asteroid impacts have long been attributed to imparting long‐lived heat in the upper crust, as well as widespread fracturing and porosity. When an impact occurs on or near an ocean environment, displaced water rushes back filling the crater and percolating down into the fractured crust. The significant heat and fracturing from impact allow for extensive hydrothermal activity. Hydrothermal alteration has been observed at the 180 km Chicxulub impact structure in Yucatán, Mexico. Previous studies estimate widespread hydrothermal transport and activity within the Chicxulub structure, but these processes are largely dependent on the assumed post‐impact permeability distribution. In this work, we present an impact simulation that tracks fragmentation as well as the generation of porosity and permeability during the Chicxulub impact event. The generation of porosity during tensile failure results in final porosities (up to 40%) that are up to a factor of 4 higher than previous models and in better agreement with drill core data. We find that both fragmentation and porosity contribute to overall permeability of the Chicxulub structure. Estimated permeabilities (up to 10−14 m2) are greater than measured values from drill cores because of the contribution from large‐scale fragmentation, which cannot be resolved in cm‐diameter drill cores. The larger porosities and permeabilities computed in this work suggest that the volume of hydrothermal activity generated by Chicxulub were 10 times more than previously estimated for Chicxulub and 100 times more than the Yellowstone caldera. Plain Language Summary: The Chicxulub impact event that led to the extinction of the dinosaurs 66 million years ago hit the Earth on a carbonate platform leaving a 180 km wide impact crater onto what is now Yucatán, Mexico. The impact caused widespread fracturing of the carbonate crust and underlying granite. The extent of this fracturing and what effect it had on hydrothermal activity is of great interest. Several drill cores have been unearthed from within the crater by scientific expeditions. In this work, we build on previous impact simulations of the event using an updated code to model and estimate the extent of fragmentation in the carbonate and granite. Specifically, we model the formation of porosity (void space) and fragmented materials and estimate permeability (the interconnectedness of void space or fractures) and compare with what has been measured and observed in the drill cores for various regions within the crater. We find that the impact likely created more permeable space than what is estimated from drill core data. More permeable space may suggest more hydrothermal activity could be sustained as water from the ocean rushed back into the fractured, warm crust. Hydrothermal systems from the Chicxulub impact may have been 100 times larger than the modern Yellowstone Caldera. Key Points: We simulate impact‐induced porosity with iSALE that is comparable to porosity measured in two different drill coresWe find the permeabilities introduced by the Chicxulub impact event may be greater than those measured from the M0077A and Yax‐1 drill coresThe output from this work will be useful and necessary for constraining the longevity and evolution of hydrothermal systems [ABSTRACT FROM AUTHOR]

As a technique capable of replacing laboratory experiments, a large number of digital rock simulations have been widely used for the characterization of reservoir petrophysical parameters. For conditions with less coring data, rapid reconstruction of three-dimensional (3D) digital rocks using two-dimensional (2D) pore structure images is an important prerequisite for the accurate calculation of petrophysical parameters. However, the conventional digital rock rapid reconstruction method with poor pore connectivity leads to the erroneous evaluation of key reservoir rock parameters (e.g., permeability and resistivity). In this study, we used the sequential indicator simulation method as the base data and combined the erosion operation and expansion operation in mathematical morphology to realize the rapid construction of 3D digital rock models with strong pore connectivity. The accuracy of the digital rock model reconstructed by the new method was verified by comparing with the permeability and electrical properties obtained by the CT-based method, sequential indicator simulation method, multi-point statistical method, process-based method, and deep leaning method. This study overcomes the shortcomings of the sequential indicator simulation digital rock reconstruction method in terms of small pore radius and poor pore connectivity, improves the permeability of constructing 3D digital rocks, and lays the foundation for accurate and rapid analysis of petrophysical properties. [ABSTRACT FROM AUTHOR]

The effective electrical conductivity of organic-rich mudrocks can be influenced by the presence of clay, pyrite, and thermally mature organic matter. In this paper, we investigate the impacts of conductivity, volumetric concentrations, and spatial distribution/connectivity of clay, pyrite, and kerogen networks on the effective conductivity of the rock and how this affects the assessment of water/hydrocarbon saturation. This quantification enables an understanding of when such components need to be considered in interpreting resistivity measurements in organic-rich mudrocks. We perform sensitivity analysis on the impacts of (a) thermal-maturity-dependent kerogen conductivity, (b) volumetric concentration/spatial distribution of kerogen, (c) conductivity and volumetric concentration/spatial distribution of pyrite, and (d) cation exchange capacities of various clay minerals and their concentration/spatial distribution on the effective conductivity of the rock. The sensitivity analysis showed that with increasing pyrite concentration, the effective conductivity of the rock increased. This increment became significant when the concentration of pyrite was above 2%. Lastly, we observed that thermally mature kerogen increased the conductivity of the rock, with a significant increment occurring when the kerogen conductivity was above 0.01 S m−1. Results confirmed that the incorporation of conductive rock components such as clay, pyrite, and kerogen into the electrical rock physics model improved the estimates of hydrocarbon reserves. [ABSTRACT FROM AUTHOR]

The lower limits of petrophysical properties for an effective reservoir are among the key parameters for assessing hydrocarbon reserves and are therefore directly related to hydrocarbon exploration and development strategies. However, the lower limits for marine sandstone gas reservoirs are still not clear and the impact factors also remain to be discussed. This study analysed the lower petrophysical property limits of an effective sandstone reservoir in the Qiongdongnan Basin using porosity, permeability and gas testing. The results showed that the lower porosity and permeability limits of effective reservoirs developed in the deltas are 8.9% and 1.2 × 10−3 μm2, respectively, and 11.3% and 4.0 × 10−3 μm2 in the submarine canyons and fans, respectively. Sedimentary facies, sediment transport distance, grain size and burial depth of sandstone significantly influence the lower physical property limits. The lower porosity and permeability limits increase with the increase in sediment transport distance as well as the decrease in sandstone grain size and burial depth. Sediment sources and sedimentary facies determine whether sandstone can become an effective reservoir in the Qiongdongnan Basin. Specifically, the sediment source dramatically influences the petrophysical properties of sandstone. The sandstone sourced from the Red River has higher porosity and permeability, followed by the sandstone sourced from the Hainan Uplift, and the sandstone sourced from the palaeo-uplift within the basin has the lowest porosity and permeability. The feldspar dissolution by CO2 and organic acid is the primary formation mechanism of the effective reservoir in the Lingshui Formation, whereas the dissolution of glauconite is more common in the sandstone reservoirs of the Sanya and Meishan formations. [ABSTRACT FROM AUTHOR]