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Abstract The key scientific problem to be solved in this paper is the optimal development and utilization model and the economic evaluation model of China's land-phase shale oil and gas resources, and the purpose of the research is to promote the large-scale commercial development and utilization of China's shale oil and gas resources, and to safeguard China's oil and gas energy security and the sustainable development of the economy. The article proposes to adopt the small surface element volume method (oil content rate method) to evaluate the pure shale oil resources, adopt the Cobb–Douglas production function model as the optimization model to measure the boundary production capacity of shale oil and gas, construct the optimal development and utilization model for shale oil and gas resources considering the five first-level safeguard indexes, namely, science and technology (A), capital (K), talents (L), reserves (S) and ecological environment (E), and establish the basic constraint model for the optimal development and utilization of shale oil and gas resources. The basic constraint model, as well as the evaluation model of economic coefficients for the development and utilization of shale oil and gas resources were established. The pure shale oil resources are mainly calculated based on the movable oil content of shale. In the paper, the S 1 of normal pyrolysis (300 °C) is regarded as movable oil, and the sum of S 1 and evaporated hydrocarbon (light hydrocarbon) loss is the movable oil content of shale. The integrated geological-physical exploration-engineering comprehensive evaluation of China’s land-phase shale oil-rich and high-yielding “sweet spot” is an important prerequisite for the realization of shale oil and gas resources to build production scale and effective development, and the least-squares method is used to estimate the average production function, the distance to the maximum value of the residuals, and the boundary capacity production function. The average production function and residual maximum distance are estimated by the least squares method, and the production function of the boundary capacity is derived, and the quotient of the boundary capacity and the actual capacity is calculated to get the capacity utilization rate, which can be used to analyze the potential of future shale oil and gas growth. The development of shale oil and gas resources in a target block requires comprehensive consideration of the first-level guarantee indicators such as science and technology (A), capital (K), talents (L), reserves (S) and ecological environment (E), as well as more than 10 s-level indicators and a number of third-level indicators, in order to ensure that the oil companies maximize their profits by organizing the development and production. The economic coefficient can be expressed as the ratio of economically recoverable resources to geological reserves. The larger the economic coefficient for the development and utilization of shale oil and gas resources is, the better the economy of the area is, and the larger the proportion of shale oil and gas resources that can be exploited. There is little special literature on the optimal development and utilization model of shale oil and gas resources and energy security among many research results at home and abroad. The evaluation of pure shale oil using the small surface element volume method (oil content rate method) and the construction of the boundary capacity calculation model, the optimal development of the basic constraints model and the economic evaluation model that we have determined, although they can not yet fully cover all the links and factors related to the development and utilization of shale oil and gas resources, are not yet fully covered by our research work. However, our research work has given the model more geological and economic theoretical connotations, and provided an economic basis and technical reference for the large-scale and commercial development and utilization of shale oil and gas resources as an effective alternative to oil imports.

Abstract To maintain performance of an aqueous-based drilling muds (ABDMs), it was imperative to understand the decay mechanism of the incorporated synthetic polymers, when exposed to the elevated temperatures. The understanding of the decay mechanism could provide a polymer replenishment strategy for the fluid to retain a specific rheology and filtrate control performance. In this context, thermal-degradation of various acrylamide co-polymers was investigated in different monovalent brines. The acrylamide co-polymers were custom synthesized, and their molecular weight and % sulfonic substitution was verified using the capillary viscometer and nuclear magnetic resonance spectroscopy techniques respectively. The co-polymer thermal degradation mechanism (i.e., polymer hydrolysis) in various monovalent brines (KCl, NaCl and NaBr) was quantified by novel titration for temperature range {121 °C, 177 °C}. The degradation response of the co-polymers was then correlated with their rheology and HPHT (high-pressure-high-temperature) filtrate performance; for instance, the titration studies showed that co-polymer degradation was 12–15% and 44–47% after sixteen hours aging at 121 °C and 177 °C respectively; correspondingly the co-polymer performance in ABDM, exhibited HPHT filtrate of 12–18 mL and 38–40 mL at those respective temperatures after sixteen hours of aging. The quantified understanding of the co-polymer thermal degradation was used to device a new approach for co-polymer replenishment strategy; it was illustrated that a 7% replenishment of the co-polymer for every eight hours, at 121 °C, enabled sustained HPHT filtrate of 12–18 mL for the studied evaluation period of thirty-two hours. The replenishment approach presented in the study would provide a valuable tool for drilling automation to ensure sustained fluid performance.

Abstract The current extension limit prediction model for offshore extended-reach well (ERW) in mudstone does not consider the formation collapse, which poses a huge risk to offshore drilling construction. To address this problem, this paper presents new open-hole extension limit prediction model for ERW. By considering formation collapse, rate of penetration (ROP), and annular pressure loss, the extension limit models during normal drilling and tripping were derived. The sensitivity of geological and engineering factors was evaluated by analyzing limits for wells 1H and 2H. The research results showed that: (1) The extension limit increases with the ROP and formation collapse duration, but decreases with the increase in mud weight, plastic viscosity, and flow rate. (2) In ERWs, the mud flow rate has a significant impact on the extension limit than the plastic viscosity of mud fluid. However, mud weight has the least impact compared to the two. (3) Considering various parameters, the predicted extension limit of well 1H, when the mud weight is 1.16 g/cm3 [9.67 ppg], is 1593.28 m [5225.96 ft] less than the limit when the collapse period is not considered.

Abstract During the drilling process, the issue of drilling fluid loss can lead to changes in the mechanical properties of the formation, thereby altering the stress environment of nearby faults. In order to assess the risk of fault activation during drilling operations, the Ordos M area shale was selected as the research object. Mechanical experiments were conducted on rock samples immersed in water-based drilling fluid with a pressure differential of 2 MPa and a temperature of 50 °C. The changes in the mechanical properties of the shale before and after immersion in drilling fluid were determined. Based on the experimental results, combined with the spring combination model and fault activation theory, a quantitative evaluation of fault activation risk was conducted. The findings revealed that the shale in this region has a high clay content, demonstrating a certain level of water sensitivity. The presence of micro-pores and micro-fractures is well-developed, increasing the interaction probability between drilling fluids and clay minerals. After immersion in drilling fluid, there was a varied decline in all mechanical strengths of the shale. The elastic modulus is positively correlated with the shear strength and Coulomb stress of the fault plane. The Poisson’s ratio is positively correlated with the shear strength and negatively correlated with the Coulomb stress. The greater the internal friction and cohesion, the higher the shear strength of the fault plane, and the larger the friction coefficient, the smaller the Coulomb stress, resulting in a more stable fault.

Abstract This study addresses the critical challenge of excessive water production in mature oil and gas reservoirs. It focuses on the effectiveness of polymer gel injection into porous media as a solution, with an emphasis on understanding its impact at the pore scale. A step-wise Lattice Boltzmann Method (LBM) is employed to simulate polymer gel injection into a 2D Berea sample, representing a realistic porous media. The non-Newtonian, time-dependent characteristics of polymer gel fluid necessitate this detailed pore-scale analysis. Validation of the simulation results is conducted at each procedural step. The study reveals that the methodology is successful in predicting the effect of polymer gel on reducing permeability as the gel was mainly formed in relatively larger pores, as it is desirable for controlling water cut. Mathematical model presented in this study accurately predicts permeability reductions up to 100% (complete blockage). In addition, simulations conducted over a wide range of gelation parameters, TD_factor from 1 to 1.14 and Threshold between 0.55 and 0.95, revealed a quadratic relationship between permeability reduction and these parameters. The result of this research indicates LBM can be considered as promising tool for investigating time-dependant fluids on porous media.

Abstract Calculating the minimum miscibility pressure (MMP) between crude oil and carbon dioxide (CO2) is critical for optimizing injection parameters, designing schemes, and predicting production capacity in CO2 injection projects for enhancing oil recovery. However, an accurate approach for obtaining this parameter is not yet established. In order to tackle this issue, a novel approach is suggested, based on the original cell-to-cell model, to determine the MMP and the 97% oil recovery rate as the standard. Using the volume-transformed Peng-Robinson equation of state enhances the precision of fluid volume estimation, as it mainly relies on predicting fluid volume within each cell. Furthermore, to ensure a precise estimation of the ultimate oil recovery rate, it is imperative to employ a total cell count of 500 in all simulations to avoid the problem of numerical dispersion. Finally, a second-order polynomial equation more accurately predicts the infinite-cell oil recovery factor. The accuracy of the modified model is verified by comparing MMP values from five oil and gas systems in the literature. The computational results of the modified multiple-mixing-cell (MMC) approach exhibit a higher level of concordance with the MMPs in the literature. The average relative error is less than 3.96%. The improved MMC algorithm can quickly determine the miscibility mechanism and visually represent the dynamic miscibility process involving multiple oil-gas contacts in a slim tube. This study provides a theoretical and practical basis for addressing the critical scientific issues of CO2-safe storage technology.

Abstract Liquid carry-over phenomenon, where liquid droplets escape with gas, is a prevalent operational challenge in gas–liquid separators. Liquid carry-over leads to foaming issue and performance reduction within separator downstream absorption processes. In order to ascertain whether liquid carry-over is inducing foaming within the gas sweetening process’s absorption tower at Iraq’s Khor Mor gas-condensate processing plant, this study initiated an evaluation of the liquid droplet size distribution in the gas product and gas/liquid separation efficiency of upstream Alpha, Bravo #1, Bravo #2, and Charlee separators that feed into the aforementioned tower by using the Horizontal Vessel and ProSeparator correlations in Aspen HYSYS v.11 software. The study revealed that Alpha and Bravo #2 experienced liquid carry-over issues. In response to these challenges, an innovative smart separator design, referred to as an adjustable separator, was proposed, employing the Arnold-Stewart semi-empirical procedure. This design allows for easy adjustment to accommodate changes in feed composition and operational conditions, mitigating the liquid carry-over problem. The smart design demonstrated a significant increase in gas/liquid separation efficiency for Alpha separator, improving by 31.11% under current conditions and 77.65% under future conditions. Similarly, under both current and future conditions, the smart design of Bravo #2 separator yielded an enhancement of 21.31% and 28.23%, respectively. These results suggest that the smart design can be considered an optimal solution for controlling liquid carry-over. This innovation not only maintains high gas/liquid separation efficiency but also prevents foaming, offering a robust solution for ensuring sustained operational performance and productivity in gas–liquid separation processes.

Abstract To solve the problem of low resolution of seismic data from granite weathering crust and difficulty in predicting effective reservoir distribution. Based on the research idea of combining geology and seismology, seismic facies characteristics and effective reservoir distribution of granite weathering crust are studied by means of frequency division reconstruction processing, seismic facies analysis and sensitive attributes interpretation. This method consists of the following four main processes: (1) Using improved Morlet wavelet function for frequency division and reconstruction processing of seismic data; (2) From the perspective of geological evolution, analyzing the geological origin of seismic facies; (3) Based on the results of well- seismic combination, clarifying the types of effective reservoirs and predicting their distribution; (4) Comprehensive research indicating favorable reservoirs distribution. The results indicate that (1) a considerably improved resolution of seismic data processed by frequency division reconstruction is obtained based on the improved Morlet wavelet function. Thus, granite reservoirs then have clearer internal reflection characteristics. (2) Affected by differences in weathering, the seismic facies in granite weathering crusts can be classified as follows: Strong-amplitude facies with amplitudes of 23,700 − 32,800, corresponding to eluvium, represents the late stage of weathering crust evolution with high-intensity weathering. Medium-amplitude facies with amplitudes of 5,250 − 24,000, corresponding to dissolution layer, represents a middle stage of weathering crust evolution with moderate weathering. And weak-amplitude-blank facies with amplitudes of 0–5,330, corresponding to disintegration layer, represents an early stage of weathering crust evolution with weak weathering. (3) Effective reservoirs can be classified according to well-seismic calibrations and combined with reservoir spaces, porosities and permeabilities, and the logging and oil-bearing characteristics of the reservoirs. Type I effective reservoir comprises medium-amplitude facies, with favorable reservoir conditions and high-yield oil-bearing properties; this type is distributed in the western slopes, with an elevation of 1,300-2,500 m. Type II effective reservoir comprises strong-amplitude facies, with poor oil-bearing properties; this type is mainly distributed in the southeast and north slopes of the study area, with a relatively limited range, and the elevation is mostly below 1,500 m. Type III effective reservoir comprises weak-amplitude-blank facies, with poor reservoir conditions and poor oil-bearing properties; this type is widely distributed at various elevations. (4) The areas where medium-amplitude facies have developed are the most favorable reservoir exploration zones for granite in Dongying Sag, Bohai Bay Basin.

Abstract In gas injection, which is one of the fascinating enhanced oil recovery techniques, the main mechanism involves decreasing interfacial tension (IFT). Although various mechanisms can affect the IFT of a system, in most experimental and numerical studies, condensation is considered the dominant mechanism among condensation-vaporization and vaporization. Investigating the impact of each mechanism is crucial as they can influence the IFT of the system and, consequently, the effectiveness of the gas injection method. This study introduces a novel model to assess the influence of different mechanisms on system IFT. The model defines system IFT, adjusts fluid relative permeability to represent miscible, immiscible, and near-miscible states, and utilizes the Buckley–Leverett method to analyze gas fractional flow and saturation profiles when injecting carbon dioxide (CO2), methane (CH4), and nitrogen (N2). Furthermore, the research explores the impact of injection pressure and IFT at minimum miscible pressure (IFT0) on gas injection efficiency. Based on our results, for both live and dead oil, the condensation mechanism reduces IFT and near-miscible pressure; switching to a condensing-vaporizing mechanism increases these parameters. This trend was consistent across all gases studied (N2, CO2, CH4), with a more significant effect observed on the CH4-live oil system compared to N2 and CO2. Controlling the condensing mechanism in IFT measurements enhances gas flow rate and relative permeability curve within the medium. Higher injection pressure in the condensing mechanism and IFT0 = 0.5 leads to faster fluid movement and improved relative permeability due to increased driving forces. Higher IFT0 accelerates the relative permeability of fluids and gas movement within the medium by promoting miscibility sooner. The impact of IFT0 was more pronounced on the dead oil–gas system compared to the live oil–gas system in this study.

Abstract Tight sandstone reservoirs are significant sources of natural gas reserves. As traditional reserves become increasingly scarce and costly, optimizing the development of these reservoirs becomes crucial. This study introduces a novel two-phase gas–water flow model for single wells, incorporating both Darcy and non-Darcy flow equations. These equations are derived from mass conservation and momentum principles for both gas and water phases. Using data from a real tight gas well, our model, which includes stress-sensitive phases for gas and water, outperforms traditional Darcy flow models. Specifically, the average relative deviations in daily production rates were 0.1815% for gas and − 0.2677% for water, which are significantly smaller compared to traditional Darcy flow models. Further application of the non-Darcy flow model reveals strategies to enhance well performance. For example, mitigating liquid lock damage within a 2 m radius near the well could restore the permeability from 0.045 to 0.143 mD, thereby tripling the daily gas production. This non-Darcy flow model is easy to implement and shows significant potential in forecasting production yields in tight sandstone reservoirs, highlighting its importance in the petroleum and natural gas industry.

Abstract Pore types in carbonate reservoirs are more complex than their sandstone counterparts due to the wide spectrum of their depositional environments and their more complicated post-depositional processes. This means that a good knowledge of pore types is vital in determining carbonate formation’s elastic and reservoir properties. This study aims to develop a multi-physics approach to determine pore-type variations in a carbonate reservoir using well log information from one of the oilfields of the Abadan Plain in southwest Iran. Firstly, we determined lithology, porosity, and fluid content by interpreting conventional well logs (gamma ray, resistivity, density, neutron, photoelectric, and P-wave sonic). Then, nuclear magnetic resonance data were used to determine different pore types within the Main Ilam and Sarvak formations. We distinguished between clay, micro, meso, and macro pore types. We confirmed our interpretation results using thin sections, scanning electron microscopy photographs, and pore-size distribution on the available core plugs. Finally, a carbonate rock physics model was employed to model sonic velocities using petrophysical interpretation along with pore-type determination results. A good match between modeled and measured sonic velocities confirmed that using nuclear magnetic resonance data for pore-type determination can reasonably estimate pore-type variations needed for rock physics modeling. The standard industry procedure for carbonate rock physics modeling uses sonic logs, core data, or thin sections to determine pore types. We offer a substitute approach with reasonable accuracy for pore-type modeling needed for carbonate rock physics modeling. We modeled pore types independently from sonic velocity and used them to predict P-wave velocity with a correlation coefficient of 92 and 64 percent accuracy in the Main Ilam and Sarvak formations. Graphical abstract

Abstract The occurrence of fluid flow near a wellhead is the major concern of the petroleum industry, as pressure drop, loss of formation, and other variables of interest are mostly affected in this region. The fluid flows from the hydrocarbon reservoir to the wellbore can be characterized as laminar to turbulent; thus, it is important to model this phenomenon with the integrated wellbore-reservoir model. Using 3D Navier–Stokes equations, an integrated wellbore-reservoir model is created in this study, and it incorporates the formation damage zone. For the porous-porous and porous-fluid interfaces, the General Grid Interface (GGI) approach is applied in conjunction with the conservative mass flux interface model. Model equations are solved using a velocity-pressure coupling solver that is pressure-based. For reliable and quick results, the system of equations is solved using an algebraic multigrid approach. The pressure diffusivity equation’s analytical solution under steady-state flow circumstances is used to validate the model. The integrated wellbore-reservoir model is applied to different reservoir scenarios, for example, different production rates, formation zones, and reservoir formation conditions. The results indicate that the present Computational Fluid Dynamics (CFD) model can be extended to simulate the real field scale model. integrated wellbore-reservoir modeling based on 3D Navier–Stokes equations with efficient computational techniques can lead the field of petroleum industries to advance current knowledge.

Abstract Condensate blockage significantly impairs gas production in low-permeability reservoirs by reducing gas relative permeability and increasing condensate saturation near the wellbore. Particularly acute in reservoirs with low pressure and permeability, effective solutions are required to mitigate this formation damage. This study introduces a novel acid treatment strategy aimed at enhancing the injectivity index in gas reservoirs afflicted by condensate blockage. Leveraging mineralogical analysis, Hydrochloric Acid (HCl) was identified as the optimal acidizing agent. The most effective concentrations of HCl for rock dissolution—15% and 7.5%—were determined through dissolution tests. The research further advances by adding methanol to the acid mix, resulting in three distinct formulations: HCl 15 wt%, HCl 15 wt% + methanol, and HCl 7.5 wt% + methanol. Comprehensive wettability alteration tests and coreflood experiments were conducted to evaluate the efficacy of these systems in permeability enhancement. The HCl 7.5 wt% + methanol formulation demonstrated superior performance in permeability improvement and condensate blockage reduction, outshining the other systems. Notably, this new acid system effectively altered wettability from hydrophobic to hydrophilic, facilitating the passage of condensate through the pore throats and thus aiding in the removal of blockages. The integration of methanol with HCl, particularly at a 7.5 wt% concentration, represents a significant advancement in the treatment of condensate blockage in gas reservoirs, promising to improve gas recovery rates by addressing the challenges posed by low-permeability formations.

Abstract Understanding the distribution of shear wave velocity (V S ) in hydrocarbon reservoirs is a crucial concern in reservoir geophysics. This geophysical parameter is utilized for reservoir characterization, calculating elastic properties, assessing fractures, and evaluating reservoir quality. Unfortunately, not all wells have available V S data due to the expensive nature of its measurements. Hence, it is crucial to calculate this parameter using other relevant features. Therefore, over the past few decades, numerous techniques have been introduced to calculate the V S data using petrophysical logs in wells with limited information. Unfortunately, the majority of these methods have a drawback they only offer insight into the location of the wells and do not provide any details regarding the distribution of V S in the space between the wells. In this article, we employed three-dimensional post-stack seismic attributes and well-logging data integration to predict the distribution of V S in the Asmari formation in an Iranian oil field. To accomplish this objective, the model-based seismic inversion algorithm was utilized to convert the seismic section into the acoustic impedance (AI) section. Then, AI and seismic data were utilized in the cross-validation method to determine the relevant attributes for predicting the spatial distribution of V S throughout the entire reservoir area, using an artificial neural network. The proposed method was shown to provide 94% correlation and 109 m/s error between the actual and estimated V S . Also, the calculated V S section has a high correlation with the actual logs at the location of the wells.

The article presents the results of the composition analysis of 27 recent (surface) pollen assemblages collected in typical plant communities in the northern part of the Central Kamchatka Depression and on the surrounding slopes of the Sredinny Range and Klyuchevskaya Sopka volcano. Our data show that spore-pollen spectra reliably represent the composition of forest plant communities. However, the proportions of pollen in the spectra of some arboreal taxas does not always correspond to their role in plant communities The adequacy of the spectra for plant communities is confirmed by cluster analysis, according to which the most statistically similar spore-pollen spectra are formed in similar plant communities. Regional components of the spectra in surface samples distort the ratios of main taxa in plant communities, especially in the high altitudinal vegetation belt. The participation of coniferous tree pollen in the spectra is underestimated compared to their actual presence in plant communities. These features must be considered when interpreting fossil spore-pollen spectra. Our materials made it possible to identify taxa whose pollen is often found in the spectra of the subalpine and alpine zones: Alnus alnobetula, Liliaceae, Polygonaceae, Asteraceae, Saussurea, and Sanguisorba. The strongest influence of local vegetation is observed in the spectra of swamps and coastal plant communities. The spectra of these communities usually contain pollen of Alnus hirsuta, Salix, and Populus, as well as Rosaceae, Cyperaceae, Comarum, Myrica, and Menyanthes, and spores of Polypodiaceae and Equisetum. Our materials will facilitate more reasonable reconstructions of Kamchatka vegetation based on the pollen analysis in the study of fossil pollen spectra of the Kamchatka Peninsula, as well as in the interpretation of pollen data from other mountainous regions.

The results of the analysis of changes in electrotelluric potentials (ETP) during the observation of intense solar flare events and intense magnetic storms on Sakhalin are presented. The data were studied in the period from July 20 to October 12, 2023. The absence of characteristic changes in the ETP (integral amplification or attenuation of noise in the low-frequency region) depending on the presence or absence of a solar flare event is shown. At the same time, in some cases, the strongest flashes were found to coincide with the appearance of signals of the GUV type (Geyser type ULF Variation). For almost three months of observations, five cases of quasi-periodic GUV series have been identified, four of which coincide completely or partially with the times of solar flares and magnetic storms. It should be noted that earlier in the literature, the appearance of these signals was not correlated with any physical process. At the same time, the identification of such patterns is an integral part of extensive work on identifying predictive signs of earthquake preparation in the ETP

This paper proposes an experimental model for predicting the intraseasonal variability of ice area in the Sea of Okhotsk, implemented as a computer program. The physical and statistical model was built on the basis of the following components: the relationship of the seasonal maximum ice area in the Sea of Okhotsk with surface air and water surface temperature parameters; the relationship between short-term fluctuations in ice area influenced by cyclonic activity during lunar syzygies; and the tendency of long-term changes in ice area series in the Sea of Okhotsk. Various data series for the period 1980–2018 were analyzed in order to build a predictive physical and statistical model. The main data sources for determining parameter relationships were the ERA-Interim and ERA5 reanalysis archives, data on air temperatures from coastal hydrometeorological stations, and five-day maps of the distribution of ice concentration published by the Japan Meteorological Agency. The predictive model algorithms were implemented in the Python programming language using additional software libraries. The model allows the calculation of predicted values of ice area during the period of its fall-winter growth from November/December until its seasonal maximum (March), with a lead time of up to four months. The input data for constructing regression equations were a long-term series of air and surface water temperature parameters, dates of lunar phase changes, and values of ice area in the Sea of Okhotsk. The output data of the model were the values of the intraseasonal variability of ice area. The model was tested for the period 2001– 2020, and the average relative error of the calculated and predicted values of ice area compared to the actual values was less than 7%. The accuracy of prediction during the period of maximum development growth and the seasonal maximum for temperate and mild winters in terms of the complexity of ice conditions was 79 %.

One of the crucial tasks in studying the genesis and deep structure of mud volcanoes is to determine the origin of the erupted material and the depth of its original location, the so-called roots. The purpose of this study was to present the first results of stratigraphic control of solid emissions from the Yuzhno-Sakhalinsk Mud Volcano with local stratigraphic units. As a result of field work, a collection of rock material sampled from the mud volcano deposits and natural outcrops of the stratigraphic units typical of the study area has been compiled. According to lithological characteristics, sandstones, siltstones, clay-bearing carbonate, and carbonate rocks have been identified among the large detrital rocks in the solid emissions of the Yuzhno-Sakhalinsk Mud Volcano. The largest group of rock fragments was represented by the sandstone, which was different in its structural and textural characteristics. The first confirmations have been obtained that the mud volcano chamber extends beyond the traditionally accepted boundaries of the Bykov Formation. The preliminary results of stratigraphic control of large detrital rocks indicate the highest lithological similarity with the deposits from the Lower Bykov Subformation and Naiba Formation, suggesting that the main source (mud volcano chamber) of the erupted large detrital rocks lies within the depth range of 2,500 to 3,500 meters. Evidence of Cenozoic rock inclusion in the mud volcano process has also been found.

The composition and ratios of main components of pollen assemblages from the surface layer of peatlands, soils, lake sediments, and alluvial silts in different parts of the Ketoi Island were analyzed. The island, despite its small size, is distinguished by a complex organization of the landscapes. The pollen spectra represent well the local vegetation at the sampling sites, regardless of the genesis of sediments. Pollen brought from adjacent territories does not have a significant effect on the composition of pollen spectra. The spectra from soil deposits in the southeastern part of the island are represented by heather pollen; in the southwestern part, by tree pollen, mostly Siberian dwarf pine, alder, and birch pollen. Among nonarborescent pollen, Asteraceae and Ericaceae are dominant. The pollen spectra obtained from pioneer soil in the western part of the island consist of club moss spores (Lycopodium clavatum), which represent communities on overgrown rockfall deposits. The assemblages of the surface layer of peatlands contain large amounts of sedge and grass pollen. The pollen spectra from alluvial silts represent the vegetation of small valleys, where alder, dwarf pine, and Erman’s birch along the sides are common. The pollen spectra from the sediments of small lakes represent local biotic communities very well. Allochthonous pollen of dark coniferous and broad-leaved trees is present in the spectra in small quantities, except for two samples. This pollen was brought from the southern islands, including those of Japan. The data obtained can be used for paleogeographic reconstructions in the analysis of the formation of pollen spectra on small oceanic islands.

The paper presents an overview of the seismicity of the southern part of the Russian Far East in 2023 based on the data from the catalog of the “Yuzhno-Sakhalinsk” Regional Information Processing Center (RIPC) of the Sakhalin Branch of the Federal Research Center “United Geophysical Survey of the Russian Academy of Sciences” (SB FRC UGS RAS). The main parameters of seismicity, such as maps of earthquake epicenters and their macroseismic events, the statistical estimation of the seismicity level (SESL'09), Benioff graphs, and density maps of nominal elastic deformation in 2023 in comparison with the previous longer time interval, are given. A brief analysis of the most significant and interesting earthquakes for detailed study is given. The seismicity of the Kuril-Okhotsk, Sakhalin, and Amur and Primorye regions remained moderate during the year, within the background values. The strongest earthquake with Mw = 6.4 occurred in the southern part of the Kuril Island arc

Abstract Relative permeability (RP) curves which provide fundamental insights into porous media flow behavior serve as critical parameters in reservoir engineering and numerical simulation studies. However, obtaining accurate RP curves remains a challenge due to expensive experimental costs, core contamination, measurement errors, and other factors. To address this issue, an innovative approach using deep learning strategy is proposed for the prediction of rock sample RP curves directly from mercury injection capillary pressure (MICP) measurements which include the mercury injection curve, mercury withdrawal curve, and pore size distribution. To capture the distinct characteristics of different rock samples' MICP curves effectively, the Gramian Angular Field (GAF) based graph transformation method is introduced for mapping the curves into richly informative image forms. Subsequently, these 2D images are combined into three-channel red, green, blue (RGB) images and fed into a Convolutional Long Short-Term Memory (ConvLSTM) model within our established self-supervised learning framework. Simultaneously the dependencies and evolutionary sequences among image samples are captured through the limited MICP-RP samples and self-supervised learning framework. After that, a highly generalized RP curve calculation proxy framework based on deep learning called RPCDL is constructed by the autonomously generated nearly infinite training samples. The remarkable performance of the proposed method is verified with the experimental data from rock samples in the X oilfield. When applied to 37 small-sample data spaces for the prediction of 10 test samples, the average relative error is 3.6%, which demonstrates the effectiveness of our approach in mapping MICP experimental results to corresponding RP curves. Moreover, the comparison study against traditional CNN and LSTM illustrated the great performance of the RPCDL method in the prediction of both S o and S w lines in oil–water RP curves. To this end, this method offers an intelligent and robust means for efficiently estimating RP curves in various reservoir engineering scenarios without costly experiments.

Abstract Horizontal drilling and multistage hydraulic fracturing have seen widespread application in shale formations during the past decade, leading to significant economic productivity gains through the creation of extensive fracture surfaces. The determination of the ideal cluster spacing in shale gas wells is contingent upon the unique geological and formation characteristics. Generally, reducing the spacing between clusters has the potential to augment gas recovery, albeit at the expense of higher drilling and completion costs, as well as the influence of stress shadows on fracture propagation. This study introduces an integrated methodology designed to explore the impact of cluster interference on well performance. Commencing with a fracture propagation model accommodating stress shadow effects for an equivalent slurry volume injection, analytical rate transient analysis (RTA) was amalgamated with reservoir numerical simulation to compute the effective fracture surface area (Aca.) for hydrocarbon production. The correlation between the effective fracture surface area determined by RTA and the actual stimulated fracture area (Aca.) derived from numerical simulations was established in relation to cluster spacing. The findings of this research reveal that wells featuring a greater number of stages and tighter cluster spacing tend to exhibit elevated cluster interference, resulting in a lower effective-to-actual fracture surface area ratio and heightened stress shadow effects impeding fracture propagation. A cluster spacing of 33 feet with six clusters per stage emerges as the optimal choice at formation permeability of 0.00005 md that decreased to 18 ft at formation permeability of 0.00001 md. ACe either stabilizes or decreases above the optimal value, suggesting that more clusters would not have a major impact on increasing the effective stimulated area. Allowing 20% interference, regardless of the permeability of the formation, maximized cumulative production while preventing thief zones and excessive cluster interference. The insights gained from this study will serve as a valuable resource for completion and reservoir engineers, enabling them to fine-tune cluster spacing to maximize well revenue in the dynamic landscape of shale gas extraction.

Abstract Multi-layer commingle production is a common development technique to improve the overall oil recovery of multi-layer reservoirs. However, this technique is mainly used at low water cut stage. Research on this technique at high water cut stage is comparatively few. Therefore, in order to improve productivity and recovery of wells, feasibility analysis of commingle production of multi-layer reservoirs in the high water cut stage is analyzed. To achieve a good commingle production result, the production layers must be optimized and inter-layer interference must be analyzed and reduced as much as possible. Factors, such as permeability, porosity, viscosity, capillary pressure, gravity, pressure difference, and water cut difference, have impact on commingle production. But it is difficult to consider all these factors. Therefore, according to the geological reservoir characteristics of X Oilfield, a model is established to simulate commingle production process, and the results are compared and analyzed. The interference degree is characterized by seepage resistance. The commingle production effect is evaluated by dimensionless oil increase coefficient, production index, and production index interference coefficient. The results show that the larger the difference of permeability ratio and water cut between multi-layers, the more severe the interlayer interference; dimensionless oil increase coefficients are all positive, it means that commingle production can achieve good oil increase effect even in the high water cut stage; the recommended technical limits for commingle production are that: permeability ratio is less than 5; commingle production timing is that water cut of low permeability layer is higher than 80%. This technique has been applied to X Oilfield, and the oil recovery increased about 2.8%, which confirmed this method feasibility.

Abstract To address the problems of wall collapse, cuttings slurrying, and scaling on the inner wall of the drill pipe, which often occur in small-diameter diamond wireline core drilling, the inhibition properties of polyvinyl alcohol (PVA) was investigated, and the formulation of solids-free drilling fluid with PVA as the inhibitor were completed. PVA has the advantages of fast adsorption and easy regulation of rheological properties Firstly the inhibition effect of PVA was compared with that of common inorganic salts (sodium chloride, NaCl, potassium chloride, KCl) by bentonite dispersion test, linear swelling test, shale rolling recovery test and mud ball immersion test in this study. Then, the inhibition mechanism of PVA was analyzed with potentiometric particle size tests, Fourier transform infrared (FT-IR) and X-ray Diffraction (XRD) measurements. Based on the outstanding inhibition performance of PVA, tackifiers and filtration reducers were preferred through the compatibility test. And finally, the effects of various contaminants on the comprehensive performance of the formulated solids-free drilling fluids were evaluated. The results showed that PVA exhibited better inhibition of clay hydration and dispersion in shale recovery and linear swelling compared to NaCl and KCl, which was particularly evident in the mud ball immersion test. FT-IR and XRD tests revealed that the inorganic salts were used to replace the cations with larger radius and high degree of hydration in the clay layer by ion exchange ti achieve the effect of clay de-watering by reducing the spacing of the clay interlayer and the electrostatic repulsion between the particles. However, PVA is strongly adsorbed on the clay surface in the form of hydrogen bonds due to its unique multi-hydroxyl chain structure, forming a hydrophobic barrier to prevent water molecules from entering the clay layer, thus inhibiting the hydration and swelling of the clay. Using PVA as an inhibitor, compounded with xanthan gum, sulfonated lignite resin and sulfonated gilsonite (FT-1), the solids-free drilling fluid is promising for use in diamond wireline core drilling in complex formations.

Abstract During oil production, the reservoir pressure declines, causing changes in the hydrocarbon components. To ensure better separation of produced phases, separator dimensions should also be adjusted. It is not possible to change the dimensions of the separator during production. Therefore, to improve the separation of the phases, the level of the separator needs to be adjusted. An intelligent system is required to ensure that the liquid level is maintained at the desired level for optimal phase separation during changes in reservoir pressure. In this study, a novel correlation is presented to measure the desired liquid level using new separator pressures. For this purpose, an intelligent system was built in the laboratory and tested in different operational conditions. The intelligent system effectively maintained the desired liquid level of the separator through a new correlation technique. The system accomplished this by acquiring new separator pressure readings collected by installed sensors. This approach helped mitigate the negative effects of the slug flow regime and minimized issues such as foam formation and over-flushing of the separator. It could achieve a 99.1% separation efficiency between gas and liquid phases. This was possible during liquid and gas flow rates ranging from 0 to 2.35 and 8–17 m3/h, respectively. The system could operate under bubble, stratified, plug, and slug flow regimes. Then the intelligent model obtained from lab experiments was integrated into the production model for the southern Iranian oil field. The smart model increased oil production by 13% and prevented the separator from over-flushing in 840 days.

Abstract Rapid, high-precision pickup of microseismic P- and S-waves is an important basis for microseismic monitoring and early warning. However, it is difficult to provide fast and highly accurate pickup of micro-seismic P- and S-waves arrival-time. To address this, the study proposes a lightweight and high-precision micro-seismic P- and S-waves arrival times picking model, lightweight adversarial U-shaped network (LAU-Net), based on the framework of the generative adversarial network, and successfully deployed in low-power devices. The pickup network constructs a lightweight feature extraction layer (GHRA) that focuses on extracting pertinent feature information, reducing model complexity and computation, and speeding up pickup. We propose a new adversarial learning strategy called application-aware loss function. By introducing the distribution difference between the predicted results and the artificial labels during the training process, we improve the training stability and further improve the pickup accuracy while ensuring the pickup speed. Finally, 8986 and 473 sets of micro-seismic events are used as training and testing sets to train and test the LAU-Net model, and compared with the STA/LTA algorithm, CNNDET+CGANet algorithm, and UNet++ algorithm, the speed of each pickup is faster than that of the other algorithms by 11.59ms, 15.19ms, and 7.79ms, respectively. The accuracy of the P-wave pickup is improved by 0.221, 0.01, and 0.029, respectively, and the S-wave pickup accuracy is improved by 0.233, 0.135, and 0.102, respectively. It is further applied in the actual project of the Shengli oilfield in Sichuan. The LAU-Net model can meet the needs of practical micro-seismic monitoring and early warning and provides a new way of thinking for accurate and fast on-time picking of micro-seismic P- and S-waves.

Abstract Pseudo threshold pressure gradient (PTPG) exists in the propped fractured reservoir, but its nonlinear flow law remains unclear. The effects of the mineral composition of shale and microstructure of fracturing fluid on PTPG were analyzed by X-ray diffraction and liquid nitrogen quick-freezing method. The results demonstrate that a proppant with a large particle size is more likely to form an effective flow channel and reduce liquid flow resistance, thus decreasing PTPG and increasing conductivity. The polymer fracturing fluid with rectangular microstructures significantly increased the PTPG supporting the fractured core. Experimental results show that the PTPG of the resin-coated sand-supported core in the fracturing fluid with a concentration of 1.2% is 245 times higher than that in the fracturing fluid with a concentration of 0.1% when the confining pressure is 5 MPa. Wetting hysteresis and the Jamin effect are responsible for the rise of PTPG in two-phase flow. The equivalent fracture width shows a good power function relationship with the PTPG. Thus, this study further explains the nonlinear flow behavior of reservoirs with fully propped fractures.

Abstract The method of segmented hydraulic fracturing in the coal seam roof has proven to be an efficient technique for coalbed methane exploitation. However, the behavior of hydraulic fractures in multilayer formations with significant differences in mechanical properties is still unclear. This paper studied the variation in hydraulic fracture width at the coal-rock interface by employing experimental method with a true triaxial hydraulic fracturing experimental system and numerical simulation method. Results revealed that the hydraulic fracture more likely to expanded along the coal-rock interface instead of break through it with the small horizontal stress difference and low flow rate injection condition. And improving the injection flow rate lager than a critical value, the hydraulic fracture tends to break through the coal-rock interface. Hydraulic fractures in both mudstone and coal beds exhibited a trend of increasing and then decreasing of fracture width at the interface. Since the strength of the coal seam was lower compared to that of the mudstone, maintaining high pressure was no longer necessary when the hydraulic fracture crossed the interface and entered the coal seam, leading to a reduction in fracture width within the mudstone. During the later stages of fracturing, the entry of proppant into the coal seam became challenging, resulting in a phenomenon characterized by excessive fluid but insufficient sand. The time required for the fracture width to traverse the proppant was found to be inversely proportional to the difference in horizontal ground stress and the flow rate of the fracturing fluid. And it was directly proportional to the modulus of elasticity, permeability of the coal seam, and interface strength. The interface strength has the greatest influence on the width of hydraulic fractures. In conclusion, this study provides valuable insights into the behavior of hydraulic fractures in multilayer formations with varying mechanical properties. The findings contribute to a better understanding of the factors affecting hydraulic fracture width within coal seams, which can ultimately enhance the efficiency of coalbed methane exploitation.

Abstract Drilling is a complex destructive action that induces vibrations due to the rock-bit interaction, which affects the overall drilling efficiency and wellbore quality. This study aims to enhance drilling efficiency by deploying artificial neural networks (ANNs) to integrate in-cutter force sensing and vibration data. Data is collected from experiments conducted with sharp cutters on rock samples of varying mechanical properties, measuring variables such as weight on bit, torque, rotational speed, in-cutter force, and vibration measurements. A scoring system is used to evaluate the drilling efficiency by coupling the mechanical specific energy and vibration modes. An ANN is trained with these variables to predict the rate of penetration and rock strength, which are also measured in the experiments to be used as ground truth. The reliability of the framework is demonstrated by testing the validity of the ANN model on samples with various mechanical properties. It introduces a reliable and swift method for determining optimal drilling parameters, supported by a sensitivity analysis to fine-tune the ANN and assess the influence of each parameter on performance. This study demonstrates that ANN could be successfully implemented to predict the rate of penetration and rock strength on a laboratory-scaled drilling rig. The results show that the ANN model accurately predicts training and testing datasets for scoring while drilling multiple layers with a correlation coefficient of 0.966. Integration of in-cutter sensing technology, vibration data, and ANN can be of significant interest and be used on field applications to provide a reliable and rapid decision about drilling efficiency.

Abstract In sedimentary basins, deep-seated overpressure conditions are frequently encountered. However, the precise origins of these overpressure conditions and the assessment of their formation times have long presented challenges. Previous studies have primarily relied on qualitative approaches to investigate overpressure origins, leading to substantial uncertainties in their findings. Based on theories such as the effective stress law, disequilibrium compaction, equilibrium depth, and nested fluid trapping containers in this paper, a new quantitative methodology is introduced for identifying the disequilibrium-compaction-induced origins of overpressure conditions. Additionally, the formation times of overpressure can be also estimated by nested fluid trapping container theory. This methodology is successfully applied to the northwestern Bozhong subbasin in the Bohai Bay Basin, China. The results indicate that the overpressure within the Dongying Formation of the northwestern Bozhong subbasin is primarily attributed to the disequilibrium compaction of mudstone, because the disequilibrium compaction of mudstone accounts for over 90% of the pressure in sandstone. Furthermore, the overpressure system in this area is not singular but comprises multiple nested relative fluid trapping containers. The application of nested fluid trapping container theory allows for an estimation of the overpressure’s formation time, although further validation of these estimates is required. It should be noted that the method proposed in this paper is particularly suited for sedimentary basins with relatively weak tectonic activity.

Abstract Acoustic impedance is the product of the density of a material and the speed at which an acoustic wave travels through it. Understanding this relationship is essential because low acoustic impedance values are closely associated with high porosity, facilitating the accumulation of more hydrocarbons. In this study, we estimate the acoustic impedance based on nine different inputs of seismic attributes in addition to depth and two-way travel time using three supervised machine learning models, namely extra tree regression (ETR), random forest regression, and a multilayer perceptron regression algorithm using the scikit-learn library. Our results show that the R 2 of multilayer perceptron regression is 0.85, which is close to what has been reported in recent studies. However, the ETR method outperformed those reported in the literature in terms of the mean absolute error, mean squared error, and root-mean-squared error. The novelty of this study lies in achieving more accurate predictions of acoustic impedance for exploration.

Abstract The installation of sand screens in open-hole completions in the wellbore is crucial for managing sand production. The main reason for using standalone screens in open-hole completions is their relatively reduced operational complexity compared to other sand control technologies. However, directly applying the screen to the bottom of the hole can lead to an incorrect screen type selection, resulting in an unreliable sand control method. To address this issue, a sand retention test is conducted to evaluate the performance of a standalone screen before field installation. Nevertheless, current sand retention test setups encounter several challenges. These include difficulties in identifying minimum retention requirements, interpreting results in the context of field conditions, and replicating field-specific parameters. The existing sand retention test introduces uncertainties, such as inaccurately replicating field requirements, inconsistent selection of wetting fluids, flow rates, and channel formation, leading to variations in the choice of the optimal screen using this test. In response to these challenges, this study aims to review the sand retention test and propose an improved sand retention method to overcome these problems. The focus of this article is to provide an in-depth analysis of previous sand retention test setups, their contributions to characterizing sand screens, and the parameters utilized in determining test outcomes. Additionally, this review outlines a procedure to investigate the impact of different particle sizes on screen erosion. Key findings emphasize the importance of using high-quality materials, proper screen design to resist damage and erosion, achieving acceptable natural packing behind the screen, and considering factors such as geology, wellbore conditions, and installation techniques. The analysis reveals that a high quantity of finer and poorly sorted sand increases sand production. The study recommends performing a sand pack test closer to reservoir conditions for better evaluation. Premium sand screens demonstrate the highest retention capacity, followed by metal mesh and wire-wrapped screens. Additionally, geotextiles show potential for enhancing sand retention, and screen design affects erosion resistance and service life.

Abstract Sequestering CO2 in depleted oil reservoirs provides one of the most appealing measures to reduce greenhouse gases (GHG) concentration in the atmosphere. The remaining liquids after enhanced oil recovery (EOR) processes, including residual oil and remaining water, lead to the main challenges to this approach. How to effectively evacuate a depleted oil reservoir by recovering not only residual oil but also remaining water is a critical consideration for this type of CO2 sequestration. This paper presents conceptual investigations concerning the methods which effectively evacuate depleted oil reservoirs from both the displacement efficiency and the sweep efficiency points of view. To improve the displacement efficiency, surfactant slug and solvent slug injection was examined using a core scale numerical model. Investigations regarding improving sweep efficiency, such as horizontal well pattern infilling and foam injection, were carried out based on a typical row well pattern. Simulation results showed that surfactant slug which modified the relative permeability and capillary pressure remarkably reduced both residual oil saturation and remaining water saturation. A CO2 slug injected before surfactant slug can help improve the oil recovery. Solvent enriched CO2 slug also remarkably reduced the residual oil saturation to as low as 2%. Horizontal well pattern infilling had great advantage for thick or inclined reservoirs, and foam slug injection greatly improved CO2 storage capacity in thin reservoirs by improving the sweep efficiency. Maximum mobility reduction (MRF) is the most important parameter to maximize the storage capacity and the benefit. The variation of CO2 storage capacity along with CO2 slug size. Larger foam slug size will play a better storage performance. The conceptual simulation investigations confirmed that depleted oil reservoirs can be effectively evacuated for CO2 storage. Depleted oil reservoirs with maximum evacuation are the best candidates for CO2 sequestrations.

Abstract This study presents a pioneering machine learning approach to continuously model fracture intensity in hydrocarbon reservoirs using solely conventional well logs and mud loss data. While machine learning has previously been applied to predict discrete fracture properties, this is among the first attempts to leverage well logs for continuous fracture intensity modeling leveraging advanced ensemble techniques. A multi-level stacked ensemble methodology systematically combines the strengths of diverse algorithms like gradient boosting, random forest and XGBoost through a tiered approach, enhancing predictive performance beyond individual models. Nine base machine learning algorithms generate initial fracture intensity predictions which are combined through linear regression meta-models and further stacked using ridge regression into an integrated super-learner model. This approach achieves significant improvements over individual base models, with the super-learner attaining a mean absolute error of 0.083 and R^2 of 0.980 on test data. By quantifying the crucial fracture intensity parameter continuously as a function of depth, this data-driven methodology enables more accurate reservoir characterization compared to traditional methods. The ability to forecast fracture intensity solely from conventional well logs opens new opportunities for rapid, low-cost quantification of this parameter along new wells without requiring advanced logging tools. When incorporated into reservoir simulators, these machine learning fracture intensity models can help optimize production strategies and recovery management. This systematic stacked ensemble framework advances continuous fracture intensity modeling exclusively from well logs, overcoming limitations of prior techniques. Novel insights gained via rigorous model evaluation deepen the understanding of naturally fractured reservoirs.

Abstract The demand for fuel from unconventional sources is increasing all over the world, however, there are still special and strict regulations regarding the methods of enhanced oil recovery as well as the content of the oil produced, including the amount of sulfur. In-situ combustion (ISC) is an attractive thermal method to enhance oil recovery and in-situ upgrading process. In this work, copper (II) oleate and copper (II) stearate were used for the oxidation of extra heavy oil with high sulfur content in the ISC process using a self-designed porous medium thermo-effect cell (PMTEC) and visual combustion tube. Using PMTEC the catalytic performances of the synthesized oil-soluble copper (II) oleate and copper (II) stearate and kinetic parameters such as activation energy using Ozawa-Flynn-Wall method were studied. The X-ray diffraction (XRD) and high-resolution field emission scanning electron microscopy were used to examine the characteristics of in-situ synthesized CuO nanoparticles during oxidation. As shown, the presence of oil-soluble copper (II) stearate and copper (II) oleate reduced oil viscosity from 9964 to 8000 and 6090 mPa˙s, respectively. Following ISC process in porous media in the presence of copper (II) oleate, the high sulfur extra heavy oil upgraded, and its sulfur content decreased from 10.33 to 6.79%. Additionally, SARA analysis revealed that asphaltene and resin content decreased in the presence of oil-soluble catalysts. During the oxidation reaction, homogeneous catalyst decomposed into nanoparticles, and heterogeneous catalyst is distributed uniformly in porous media and played an active role in the catalytic process. It should be noticed that, these kind of oil-soluble catalysts can be novel and highly potential candidates for initiation and oxidation of extra heavy oil in order to decrease the viscosity, enhanced oil recovery and production of the upgraded oil. Graphical abstract

Abstract The critical pressure (P c) and critical temperature (T c) of shale gas depend on the characteristic pore size because of the importance of fluid–rock interactions in the matrix. This size dependency is neglected in highly permeable formations, where gas composition is only implemented because the fluid–fluid interactions are dominant. This study determines the critical properties by accounting for the characteristic pore size in the shale matrix and gas composition. The analyzed components are carbon dioxide, ethane, methane, n-butane, nitrogen, pentane, and propane. It shows that the bulk properties overestimate the actual critical properties. The overestimation varies between 15 and 26% in a uniform 5 nm conduit with a circular cross section, and it increases nonlinearly when decreasing the conduit size. Overestimation versus size is presented to provide a convenient tool for correcting the existing data. This study also determines the critical properties of Midra shale by accounting for the pore-throat size and pore-body size distributions. The former distribution is based on the mercury injection capillary pressure measurements of eight samples, whereas the latter is based on the nitrogen adsorption measurements of six samples. This study indicates that common bulk properties overestimate the critical properties of the studied shale between 5 and 22%. The results have applications in characterizing multiphase transport in shale gas reservoirs.

Abstract The integrity of shale gas wells is crucial in ensuring safety and efficiency throughout the development process. Such integrity spans the entire process of drilling and fracturing horizontal wells and is an essential indicator for ensuring safe and stable production throughout the lifespan of the well. This study investigates methods for assessing the integrity of shale gas wells by employing the analytic hierarchy process combined with experimental data to establish evaluation criteria and weights. The assessment is carried out specifically on shale gas wells in Changning Block. Results indicate that the integrity of these shale gas wells is influenced by various factors, such as drilling and fracturing processes. Moreover, the integrity assessment of indicators such as oil layer casing/technical casing, liquid carrying capacity, and tube column deformation is relatively low, indicating a need for enhanced monitoring and management. The comprehensive evaluation results indicate that, overall, the integrity rating of shale gas wells is generally considered “common,” but some potential safety hazards still remain that require timely attention and resolution. Case analysis reveals varying levels of integrity risks in shale gas wells. Case 1’s score of 93.51 warrants attention but is still deemed generally safe. However, Case 2’s score of 73.89 indicates a disaster level, emphasizing urgent intervention needs. Critical factors such as pressure, cementation quality, and corrosion demand proactive management for safe, sustainable operations.

Abstract To avoid or mitigate the unwanted water and gas content, inflow control devices (ICDs) are designed and installed in the well to disturb the water and gas breakthrough which are trying to overtake the oil inflow, water and gas coning and sand production. Smart wells with permanent downhole valves such as ICDs are used to balance production and injection in wells. A paramount issue regarding using downhole control devices is determining the required cross-sectional area of them for control of the imposed pressure drop across the device to stabilize the fluid flow. Current methods for calculating the opening size of the ICDs are mainly based on sensitivity analysis of the ICD flow area or optimization algorithms coupled with simulation models. Although these approaches are quite effective in oil field cases, they tend to be time-consuming and require demanding system models. This paper presents a fast analytical method to determine the ICD flow area validated by a genetic algorithm (GA). Analytically, a closed-form expression is introduced by manipulating Darcy’s law applicable to multi-layer injection wells with different layer properties to balance the injection profile in the reservoir pay zone, based on equalizing injected front velocity in layers with different permeability. Considering various scenarios of analytical technique, GA optimization, and sensitivity analysis scenarios for ICD cross-sectional area determination, results for oil recovery, water production, water breakthrough time, and net present value (NPV) are discussed and compared. NPV values obtained by both analytical and GA approaches are virtually identical and greater than those of other scenarios. Compared to the base field case, the analytical method improved the oil recovery by almost 1%, reduced water production by almost 91%, and synchronized the water breakthrough time of high- and low-permeability layers (from a ratio of 1.76–1.06). The proposed analytical solution proved to be capable of providing desirable results with only one reservoir simulation run in contrast to GA and sensitivity analysis scenarios which require iterative simulation runs. The proposed analytical solution outperformed the GA as it is less computationally demanding in addition to its success in case of lowering water production for the field data. The findings of this study can help for a better understanding of the situation where water injection into the oil reservoir is problematic as the layers present different permeabilities which can induce problems such as early water breakthrough from the more permeable layer and hinder the success of the water injection process. Using ICDs and a faster and more accurate approach to calculate its cross-sectional area such as the analytical method that was used in this study can greatly increase the success rate of water injection in case of oil recovery and lower the amount of the produced water.

Abstract Temporary plugging diversion fracturing in multistage horizontal well is normally used to improve stimulation efficiency and increase production in unconventional reservoirs. Temporary plugging agent plays an important role in diversion fracturing. A strongly resilient temporary plugging diversion agent can improve the effectiveness of fracturing diversion. Therefore, a novel organosilicon temporary plugging diversion agent (QBZU) was developed through micellar copolymerization method. Self-synthesized strongly resilient temporary plugging diversion agent (QBZU gel) was prepared by using acrylamide, N, N′-methylene bisacrylamide, surfactants, organosilicon, ammonium persulfate and sodium bisulfite as chemical raw materials. The micellar copolymerization is investigated to overcome the incompatibility of hydrophobic organosilicon and water-soluble monomer by adding some appropriate surfactants. The experimental results indicated that the combination of sodium dodecyl sulphonate and Tween 80 provided excellent copolymerization results. The characteristics of compressive resistance, salt resistance, shearing resistance, resilience and degradation are superior compared with traditional rigid granular temporary plugging agent widely used in oilfields (QG hydrogel). According to the experimental evaluation results of QBZU, its pressure-bearing capacity can reach 56.3MPa, shearing strength can reach 410N, elastic modulus can reach 80MPa, and Poisson ratio can reach 0.48. Meanwhile, the main synthetic factors affecting the resilient performance of QBZU were investigated, including polymer concentration, organosilicon concentration and the types of surfactant. Based on the fracturing pressure curve and microseismic monitoring results, the plugging and fracture diversion effectiveness was further confirmed.

Abstract Integrating petrophysical and geomechanical parameters is an efficient approach to evaluating shale gas reservoir potential. The high cost of corings and their limited number, coupled with time-intensive investigation, led researchers to use this alternative combination approach. In the Jiaoshiba area, from single-pilot well core data and log measurements, petrophysical and geomechanical parameters such as shale volume, total organic carbon, gas content, as well as pore pressure, stress components, and mineral brittleness were first estimated using established methods. In the second phase, based on logging curves, the reservoir electro-facies (EF) classification was performed using the unsupervised multi-resolution graph-based clustering method on a series of twenty wells, identifying five EF with different intrinsic characteristics. Unsupervised analyses were developed using the multilayer artificial neural network while incorporating the K-nearest neighbors and graphical classification algorithms. The results from the first and second phases indicate reservoir richness in organic matter, with the best reservoir exhibited by EF2 and EF3. In addition, effective stress components (S V, S H, and S h) evaluation shows a normal stress regime with hydraulic fracture systems perpendicular to the minimum horizontal stress at each measured depth of the reservoir (S v > S H > S h). This research workflow can efficiently evaluate shale reservoirs with a realistic approach for identifying favorable fracturing positions while reducing errors due to human interference.

Abstract Shale oil development in Ordos Basin, China, primarily relies on the displacement of crude oil during the post-fracturing shut-in stage (PFSIS) of horizontal wells. Reservoir wettability significantly influences the shut-in duration and even the development approach. However, due to strong heterogeneity and super tight characteristics, the reservoir usually shows an mixed wettability, and it was usually hard to differentiate the wettability in different pore sizes. With this in mind, this study focuses on core samples from shale oil reservoir in the Longdong region of the Ordos basin to quantitatively analyze the reservoir wettability. Amott method combined with nuclear magnetic resonance is adopted in the paper to meed this end. And the optimal post-fracturing shut-in duration for Huachi and Heshui areas in the Longdong region are determined based on both wettability and field practice analysis as well as numerical simulations. Qualitative wettability evaluation reveals that the reservoir in the Longdong region is weakly oil-wet (oil-wet pores account for 58.9% and water-wet pores for 41.1%), and that larger pores are more water-wet, while smaller pores are more oil-wet. Field practice observes a noticeable two-stage decline in wellhead pressure, with pressure drop rates and water content decline rates following the order of neutral reservoir > weakly oil-wet reservoir > oil-wet reservoir during the post-fracturing shut-in stage. Numerical simulations indicate that the determination of the optimal post-fracturing shut-in duration for horizontal wells should consider reservoir properties, wettability, and injection volume. The final optimal shut-in durations for the Huachi and Heshui areas in the reservoir are determined to be 36 days and 43 days, respectively. Our study qualitatively distinguishes the wettability in different pores sizes and thus determines reasonable post-fracturing shut-in durations in different areas in Longdong region. The research has major implication for building a realistic method of wettability analysis in shale or tight oil reservoir.

Abstract The 6th member of the Triassic Yanchang Formation, hereafter referred to as Chang 6 reservoir, in the Wuqi area of the Ordos Basin presents formidable obstacles for efficient tight oil development. This reservoir is known for its tight lithology, strong heterogeneity, inadequate oil saturation, and abnormally low reservoir pressure, which collectively contribute to the highly differentiated mobility of tight oil within the formation. To overcome these challenges, a comprehensive understanding of the factors influencing oil mobility is essential. This study investigates the occurrence characteristics of movable fluids in different diagenetic facies and the corresponding influential factors by employing various microscopic experiments, including high-pressure mercury intrusion, constant-rate mercury intrusion, nuclear magnetic resonance test, scanning electron microscopy, pore-casted thin section analysis, and X-ray diffraction measurement. There is a weaker correlation between the pore-throat radius ratio and the movable fluid saturation in reservoirs of various diagenetic facies (R 2 = 0.6104), whereas there is a stronger correlation between movable fluid saturation and throat radius (R 2 = 0.9415). Among the seven types of diagenetic facies, chlorite membrane cementation-intergranular pore facies (Facies I) and chlorite and illite membrane cementation-intergranular pore facies (Facies II) have the best-developed throats and the highest coordination number. Illite cementation-intergranular pore facies (Facies III) and illite and chlorite membrane cementation-dissolution facies (Facies IV) demonstrate smaller pore-throat radii and moderate to poor reservoir connectivity. The other three facies, namely illite cementation-dissolution facies (Facies V), illite cementation facies (Facies VI), and carbonate tight cementation facies (Facies VII) exhibit underdeveloped pore structures and lower recovery rates. Pore-throat radius emerges as the principal factor influencing reservoir permeability and storage capacity. The distribution of favorable diagenetic facies is influenced by depositional environments, diagenetic processes, and microscopic pore-throat characteristics. This study significantly enhances our understanding of the differential occurrence characteristics of fluids in different diagenetic facies in the Chang 6 reservoir, providing valuable insights for future exploration and production endeavors aimed at optimizing oil recovery in tight sandstone reservoirs.

Abstract To investigate the percolation mechanism of tight sandstone reservoirs, qualitative and quantitative methods are applied to analyze the pore structure of the Ordos Basin through scanning electron microscopy and high-pressure mercury injection. Based on gas–water relative permeability data and the visualization of real sandstone models, a gas–water displacement experiment was carried out to simulate the percolation mechanism and fluid distribution of different pore types. The results show that: ① The percolation of different pore types varies greatly, and the irreducible water saturation decreases when the reservoir properties improve. The relative permeability of gas at an irreducible water saturation increases, the width of the two-phase percolation area increases, and the percolation ability is enhanced as the reservoir properties improve. ② The gas–water displacement mode changes from fingering to uniform displacement with the improvement of pore type, which is beneficial to the formation of effective reservoirs filled with natural gas under the same hydrocarbon generation conditions. ③ The time required for the pressure relief of samples with good reservoir properties is short, and the recovery is higher with the improvement of pore type. ④ The residual water in samples with a poor pore type increases, which decreases the relative permeability of gas and recovery. A reasonable development pattern should be carried out, and the production pressure difference should be strictly controlled to maximize productivity. This study provides theoretical guidance for the development of tight sandstone reservoirs in the Ordos Basin.

Abstract In fractured reservoirs, the fracture network provides the main path for fluid flow. Appropriate estimation of the fracture permeability influences the precise prediction of the reservoir’s future performance. Commonly, for a known geometry of natural or induced fracture, the permeability is estimated by applying local cubic law. One major drawback of this approach is that the fracture surface roughness, which has a significant effect on fracture permeability, is not considered. Moreover, the knowledge about the impact of fracture surface roughness on fracture permeability is not currently sufficient. In this research, the fluid flow in fractures with rough-walled surfaces was studied using computational fluid dynamics. For this purpose, the fluid flow through fractures was simulated by applying appropriate roughness for fracture walls. Furthermore, two correlations, based on response surface methodology and power-law models, were proposed to predict fracture permeability as a function of four independent variables (surface roughness, fracture aperture, angle, and porosity). The results of the two presented correlations were validated, and the statistical analysis indicates that both models are appropriate to predict fracture permeability. The findings of this study will be of great assistance with understanding and characterization of the fluid flow in rough fractures and can be used in future works.

Abstract Fracture identification and evaluation requires data from various resources, such as image logs, core samples, seismic data, and conventional well logs for a meaningful interpretation. However, several wells have some missing data; for instance, expensive cost run for image logs, cost concern for core samples, and occasionally unsuccessful core retrieving process. Thus, a majority of the current research is focused on predicting fracture based on conventional well log data. Interpreting fractures information is very important especially to develop reservoir model and to plan for drilling and field development. This study employed statistical methods such as multiple linear regression (MLR), principal component analysis (PCA), and gene expression programming (GEP) to predict fracture density from conventional well log data. This study explored three wells from a basement metamorphic rock with ten conventional logs of gamma rays, thorium, potassium, uranium, deep resistivity, flushed zone resistivity, bulk density, neutron porosity, sonic porosity, and photoelectric effect. Four different methods were used to predict the fracture density, and the results show that predicting fracture density is possible using MLR, PCA, and GEP. However, GEP predicted the best fracture density with R2 > 0.86 for all investigated wells, although it had limited use in predicting fracture density. All methods used highlighted that flushed zone resistivity and uranium content are the two most significant well log parameters to predict fracture density. GEP was efficient for use in metamorphic rocks as it works well for conventional well log data as the data is nonlinear, and GEP uses nonlinear algorithms.

Abstract The formulation of an effective development plan, optimizing exploitation efficiency, relies heavily on accurate reservoir characterization. However, existing reservoir classification methodologies, which rely on macroscopic geological observations and well-logging data, have limitations in data availability and fail to capture micro-scale pore structure characteristics accurately. The emerging technology of digital rock, widely employed in the petroleum industry, also faces challenges in accurately capturing reservoir heterogeneity due to its single-scale nature and limited application for reservoir classification. To overcome these challenges, this study presents an innovative reservoir classification approach based on the multi-scale digital rock method. This approach integrates qualitative assessment of micro-CT images for particle contact relationships and pore types with quantitative evaluation of multi-scale characteristic parameters, obtained from micro-CT and scanning electron microscopy (SEM) images. The proposed classification method demonstrates excellent agreement with the prioritization of development and production data for offshore sandstone reservoirs. By establishing a robust evaluation methodology, this classification method facilitates exploration potential assessment and development strategy optimization within the field.

Abstract Rock typing plays a crucial role in describing the heterogeneity of the reservoir. Most of the conventional rock typing methods are implemented to classify the target reservoir into various rock types based on various petrophysical properties (e.g., porosity and permeability), but fail to provide more critical information that significantly affects the final performance of the reservoir characterization including: (1) the porosity and permeability contribution of each rock type and (2) the geological genesis of each rock type. Along with the universal application of various imaging devices, the image-based microscale rock typing (IMRT) can be directly conducted based on the observed pore structures which fundamentally determine the rock types. The IMRT belongs to the computer vision field which can be divided into pattern recognition-related rock typing (PRRT) and texture segmentation-related rock typing (TSRT). The PRRT is mainly used to identify the category (e.g., lithofacies, reservoir zone, or Dunham textures) of a given rock sample. The TSRT aims to classify a single image into several areas where each area denotes a relatively homogeneous porous structure. In this paper, the popular IMRT methods and their applications are reviewed thoroughly. Many successful applications proved that IMRT is an effective way to quantitatively estimate the porosity and permeability contributions of each rock type in a heterogeneous rock sample with the help of numerical flow simulation. Besides, the IMRT results also can be used to reveal the geological genesis of each rock type when its texture is determined by a special geological process.

Abstract Near miscibility widely exists in carbon dioxide (CO2) injection development projects. However, there is no existing approach to quantify the effect of near miscibility on oil recovery. In this paper, slim tube experiments were conducted to study near miscible region. The oil displacement efficiency curve is divided into immiscibility, near miscibility and miscibility. And three linear function is obtained, respectively. Then, the space between production well and CO2 injection well is discrete to characterize the effect of near miscibility on oil recovery. Then, a new approach is proposed to calculate oil recovery of CO2 displacement in tight oil reservoirs. This approach can calculate oil recovery considering near miscibility. It is found that minimum miscibility pressure (MMP) without considering near miscibility is 4 MPa lower than considering near miscibility. The near miscible pressure range is from 0.77 times to 1 time MMP considering near miscibility. Oil displacement efficiency difference reaches to be the maximum when the pressure is the minimum miscibility pressure without considering near miscibility. The maximum of the oil displacement efficiency difference is 3.4%. The optimal formation pressure considering near miscibility is 5 MPa larger than that without considering near miscibility. The oil recovery considering near miscibility is from 0.9 to 1.3% lower than that not considering near miscibility. It reaches to be the maximum when the pressure is the optimal formation pressure level without considering near miscibility. The maximum of the oil recovery difference is 1.3%.

Abstract Underbalanced foam drilling (UBFD) represents a pivotal technique aimed at enhancing safety and operational efficiency within drilling operations. Despite its recognized benefits, the challenge of maintaining foam stability persists, particularly in conditions characterized by elevated water salinity and alkalinity. This study endeavors to bridge this gap by introducing the eco-friendly Gemini surfactant (GS12) for drilling foams and evaluating its performance under mildly alkaline conditions. Employing a dynamic foam analyzer, diverse foam properties of GS12 foams were systematically assessed, including stability, foamability, and bubble structure. Results elucidate that the optimal surfactant concentration for maximal foam stability stands at 1.5 wt%; however, a threefold concentration increase (from 0.5 to 1.5 wt%) merely yields a 30% improvement, emphasizing the economic viability of a 0.5 wt% concentration for practical UB applications. Additionally, the study demonstrates a correlation between foam stability and water salinity, with seawater exhibiting a twofold reduction in foam half-life compared to deionized water (decreasing from 27 to 13 min), mitigated by the addition of PAC polymer, which increases foam half-life from 13 to 56 min. Moreover, GS12 + PAC foaming systems exhibit surpassing stability compared to a typical commercial blend, boasting a 78% increase in foam half-life (245 min) and a 21% increase in initial foam volume (245 mL), thereby positioning it as a promising candidate for UB drilling applications. The introduction of GS12 for UB drilling and its comprehensive evaluation under mildly alkaline conditions underscore its potential for sustainable foam drilling, advocating for the utilization of environmentally friendly surfactants and green polymers to enhance drilling sustainability and address pressing industry challenges.