Search Results (425)

Reservoir fracability evaluation is critical for tight reservoir hydraulic fracturing optimization. This study introduces a novel physics-based fracability evaluation framework integrating stacking ensemble learning (SEL) and the marginal effect of the conditional expectation (MECE). First, a multidimensional indicator system was established, covering characteristics such as reservoir geomechanics, rock mechanics, and the development of natural fractures. Second, SEL models were developed to predict open flow capacity, and four performance metrics were compared to select the optimal model from 26 SEL candidates. Finally, to quantify the individual contribution of each fracability indicator while eliminating interference from treatment and petrophysical parameters, the MECE approach was adopted, thereby developing a new fracability model that quantitatively describes the reservoir’s ability to achieve greater stimulated reservoir volume (SRV) under similar hydraulic fracturing parameters. The experimental results indicate that the RF+KNN model demonstrates optimal performance in both prediction accuracy and model stability. Comparing the fracability index with microseismic monitoring data, the linear correlation coefficient between the fracability index and SRV reached 92%, validating the reliability of the fracability evaluation model. This framework provides a transferable interpretable tool for selecting reservoir sweet spots and fracturing parameter optimization. Full article

Accurate quantification of mineralogical composition in carbonate rocks is essential for reservoir characterization in the oil industry, directly influencing petrophysical properties such as porosity and permeability. However, traditional methods such as X-ray diffraction (XRD) are destructive and provide limited spatial sampling. The aim of this study was to develop and validate a workflow for the continuous quantification of calcite and dolomite in drill cores from the Brazilian pre-salt oil province by integrating short-wave infrared (SWIR) hyperspectral imaging (HSI) and Machine-Learning algorithms. A total of 80 m of cores were evaluated using 170 XRD-validated samples to calibrate linear, nonlinear, and ensemble models. The results showed that the combination of Multiplicative Scatter Correction (MSC) preprocessing with Multilayer Perceptron (MLP) and Support Vector Regression (SVR) achieved the best performance, reaching an $R^2$ of 0.84. Explainable Artificial Intelligence (SHAP) confirmed the relevance of diagnostic bands between 2330 and 2360 nm, improving geological interpretability of the predictions. The proposed methodology provides a non-destructive and high-resolution alternative for mineralogical profiling, supporting the evaluation of complex reservoirs and decision-making in the oil and gas industry. Although the workflow was validated using a specific pre-salt dataset, future studies should assess its transferability to other carbonate reservoirs and broader geological settings. Full article

The Linhe Formation of the Paleogene in the Linhua Well area of the Hetao Basin is a key target interval for hydrocarbon exploration, but strong heterogeneity caused by depositional and diagenetic modification complicates reservoir prediction. This study integrates core observations, thin-section petrography, SEM, clay mineral XRD, vitrinite reflectance (Ro), routine petrophysical data, and conventional well logs to characterize sedimentary microfacies and diagenesis, constrain the diagenetic stage and paragenetic sequence, establish a well-log-based diagenetic facies recognition model, and reveal the spatial distribution of diagenetic facies. The reservoirs are dominated by lithic arkoses and feldspathic litharenites with moderate compositional and textural maturity. Sedimentary microfacies mainly include a subaqueous distributary channel, front sheet sand, and interdistributary bay. The reservoirs are presently overall in mesodiagenetic stage A. Compaction and cementation are the principal destructive processes, whereas dissolution is the main constructive process. Quantitative evaluation shows that COPL ranges from 14.3% to 31.6% (average 25.2%), CEPL from 5.3% to 18.7% (average 12.7%), and ICOMPACT from 0.47 to 0.80 (average 0.66), indicating that compaction contributed more to porosity loss than cementation. Four diagenetic facies were identified: strongly compacted–weakly cemented, moderately compacted–strongly cemented, moderately dissolved–moderately cemented, and weakly compacted–weakly cemented. Fisher’s linear discriminant model based on GR, AC, DEN, and CNL logs achieved an overall recognition accuracy of 80.0%. Spatially, high-quality reservoirs are mainly developed in the central–southern subaqueous distributary channel belts dominated by the weakly compacted–weakly cemented facies and flanked by moderately dissolved–moderately cemented facies. High-quality reservoir development is controlled by the coupled effects of depositional microfacies, differential compaction–cementation, and local dissolution. Full article

The thermal conductivity (λ) of porous rocks as a function of total porosity, grain size, and fluid saturation is measured and modeled by combining high-precision experiments with a Staged Differential Effective Medium (SDEM) modeling framework. A 1-D divided-bar apparatus with computer-controlled guard heaters with an integrated ultrasonic pulse-transmission system was developed to measure the thermal conductivity and P and S-wave velocities simultaneously. Measurements were made on Fontainebleau sandstone cores and quartz sand packs of varying grain size and effective stresses up to 2000 psi. The sample properties were measured in both dry and water-saturated states. The SDEM model performs significantly better at predicting the saturated thermal conductivities in the sand packs. For the sand packs, the thermal conductivity and compressional velocity are the highest and most stress-sensitive for the fine-grained material. In contrast, the shear velocity is largest in the coarse-grained material. The SDEM model is adapted from previous acoustic models for use in understanding thermal conductivity. These joint models accurately reproduce the evolution of both thermal conductivity and bulk modulus during increasing compaction and varying saturation. A single parameter fits both the dry and saturated data, which allows Gassmann-style fluid substitution for the thermal conductivity. This model improves the prediction of in situ thermal conductivity from sonic well logs. Full article

Recently, a substantial quantity of oil and gas has been discovered in the pre-salt Lower Cretaceous microbialite successions of Brazil’s Santos Basin, thereby prompting a global surge in research related to microbialites. It has been demonstrated that microbial shoal reservoirs yield the highest hydrocarbon production, with optimal reservoir properties, as evidenced by experience in the field of oilfield production. However, as research progresses, it has become increasingly evident that significant heterogeneity exists in both the lithology and physical properties within microbial shoal bodies. In order to address the identified knowledge gap, the present study employs systematic petrological and petrophysical datasets. These include 30-m continuous core samples, thin-section analyses, routine petrophysical tests and mercury injection capillary pressure (MICP) measurements. The aim is to characterize the internal microfacies architecture and reservoir heterogeneity of microbial shoals. It is imperative to ascertain the principal factors that govern the heterogeneity observed in these reservoirs. This critical step is essential for a comprehensive understanding of the subject matter. The results of the study demonstrate that: the Barra Velha Formation microbial shoals in the Santos Basin can be subdivided into three microfacies, which are delineated from base to top. The foundation of the shoal is the shoal base. The rock composition is dominated by the presence of spherulites, with intracrystalline pores functioning as the primary reservoir spaces. The compositional rocks of the shoal flank are poorly sorted microbial debris, with intergranular and intragranular pores formed by penecontemporaneous dissolution. The sedimentary succession of the shoal core is characterized by well-sorted microbial debris rocks displaying multiple shallowing-upward sequences, with reverse-graded textures. The primary storage space is constituted by fabric-selective pores from penecontemporaneous dissolution, though these are subject to local disruption by destructive silicification. Meanwhile, the microbial shoals demonstrate wide porosity (8.8–26.4%, mean 16.8%) and permeability (0.13–839 mD, mean 169 mD) ranges, thus classifying them as medium-porosity, high-permeability reservoirs. The superimposition of microfacies and diagenetic processes gives rise to considerable reservoir heterogeneity. It is evident that the shoal core microfacies exhibits robust energy and substantial grain size, characteristics that facilitate its exposure above lake level during periods of high-frequency lake-level oscillation. This exposure is further compounded by the influence of atmospheric water dissolution, which remodels the microfacies during the quasi-contemporaneous period. The reservoir quality is optimal, exhibiting the highest proportion of large pores. The reservoir properties of the shoal flank are closely followed by medium and large pores, and those of the shoal base are the worst, with micro and medium pores. Full article

Tight oil reservoirs are characterized by poor petrophysical properties. After hydraulic fracturing, the low flowback rate of fracturing fluid readily leads to the formation of a water invasion zone in the near-wellbore region, which severely restricts the performance of Carbon dioxide (CO₂) huff-n-puff. To clarify the damage mechanism of the water invasion zone on CO₂ huff-n-puff in tight oil reservoirs and determine the key regulatory parameters, tight cores with a relative water invasion zone length Δδ = 0.3 were adopted as the research subject. Five groups of injection–soaking–production time combinations were designed, and single-factor analysis was implemented using the control variable method. Integrated with numerical simulation and nuclear magnetic resonance (NMR) testing, the influence of the water invasion zone, pore crude oil mobilization characteristics, and parameter regulation effects were systematically explored. The results demonstrate that the water invasion zone occupies effective pore throats to form a continuous water-phase barrier, hindering CO₂ seepage and mass transfer. After four huff-n-puff cycles, the cumulative recovery factor of the water-invaded model is 4.13 percentage points lower than that of the water-free model. After four huff-n-puff cycles, the cumulative recovery factor of the water-invaded model is 4.13 percentage points lower than that of the water-free model. The NMR T₂ spectra of cores with and without water invasion exhibit remarkable discrepancies: the water-free core presents a unimodal structure, while the water-invaded core features a distinctive bimodal structure, with obvious staged characteristics in crude oil mobilization. The recovery factor declines nonlinearly and sharply with the increase of Δδ, verifying that the water invasion zone length is the dominant controlling factor. The regulation effects of injection, soaking, and production time differ significantly: injection time serves as the pivotal parameter for enhancing oil recovery. Prolonging injection time can strengthen displacement intensity and dismantle the water-phase barrier, thereby elevating the recovery factor, whereas soaking time and production time have no significant improvement effect. The results can provide valuable references for the parameter optimization of CO₂ huff-n-puff in water-invaded tight oil reservoirs. Full article

Reservoir characterization of the Abu Roash “G” (AR/G) Member in the Karama Field, Abu Gharadig Basin, Western Desert of Egypt, is complicated by structural deformation, facies variability, and lithologic heterogeneity, which introduce uncertainties in reservoir evaluation and hydrocarbon estimation. This study aims to provide a comprehensive reservoir assessment through an integrated three-dimensional (3D) static modeling workflow. Well-log data from four wells were combined with the interpretation of seventeen seismic lines to construct structural, stratigraphic, and petrophysical models of the AR/G reservoir. The results indicate that reservoir thickness ranges from 9 to 14 ft and is structurally controlled by nine normal faults forming a horst–graben configuration that significantly influences compartmentalization and hydrocarbon distribution. Petrophysical modeling reveals favorable reservoir quality, with effective porosity ranging from 14% to 20%, an average shale volume of approximately 19%, and hydrocarbon saturation averaging 56%. Two prospective zones were identified, with estimated original oil in place (OOIP) of 10.76 MMSTB and 3.23 MMSTB, respectively, representing recoverable volumes within structurally defined closures rather than the entire field volume. The model also explains the relatively poor performance of Karama-5 and Karama-11 wells due to their peripheral structural positions outside the main closures and their higher water saturation (44–53%). These findings demonstrate that integrated structural and petrophysical modeling improves reservoir understanding and helps identify optimal drilling targets in structurally complex reservoirs of the Abu Gharadig Basin and comparable North African settings. Although the estimated volumes correspond to relatively small accumulations, they are considered economically viable within mature basins such as the Abu Gharadig Basin, where existing infrastructure and optimized development strategies enable efficient exploitation of marginal reserves. Full article

The West Junggar region in Xinjiang, NW China, hosts more than 100 gold deposits, most of which are shallow and nearing depletion. To assess deep mineralization potential, we integrated in situ sulfur isotope geochemistry with audio-frequency magnetotelluric (AMT) surveys at three representative deposits (Hatu, Baogutu, and Baogutu XI). Sulfide δ³⁴S values (0.46–4.16‰) indicate a deep magmatic–hydrothermal source. Petrophysical measurements reveal systematic resistivity contrasts that correlate with sulfide content. AMT surveys effectively delineate low-resistivity anomalies corresponding to mineralized zones, with persistent anomalies extending beneath known orebodies and along fault belts. These anomalies display two distinct geometric patterns: steeply dipping faults with en echelon fractures (Hatu) and S-shaped dip-transition zones (Baogutu and Baogutu XI), both reflecting structural controls on mineralization. The identified anomalies define probable mineralized zones at depth, suggesting significant undiscovered potential. This integrated geochemical and geophysical evidence provides compelling targets for deep exploration in the West Junggar region. Full article

The multi-cycle high-rate injection and production operations in Underground Gas Storage (UGS) facilities converted from depleted fracture-pore carbonate gas reservoirs induce complex rock–fluid interactions that threaten long-term integrity and performance. This study experimentally investigates the petrophysical responses of the Xiangguosi (XGS) UGS carbonate reservoirs in China using multi-cycle stress sensitivity tests, fines migration experiments, and water evaporation–salt precipitation analyses. SEM observations distinguish the contributions of crack closure and matrix compression to permeability evolution. Results show a sharp contrast in mechanical damage: high-quality rocks present negligible permanent deformation (<8% Young’s modulus reduction), whereas poor-quality rocks suffer catastrophic deterioration (>60%). Fines migration exhibits a three-stage behavior under cyclic flow, with water saturation significantly aggravating permeability impairment. A critical salinity threshold (220,000 ppm) is identified for the transition between drying-enhanced storage and salt plugging. Permeability declines sharply despite a slight porosity increase due to selective salt clogging of key pore throats, revealing a clear porosity–permeability decoupling. Salt deposition under movable water conditions can reduce UGS capacity by up to 1.45%. Reservoir heterogeneity, microfractures, karst structures, and initial petrophysical properties dominate the storage and flow space evolution. This work provides a predictive framework for optimizing injection–production strategies and improving the performance of complex carbonate UGS. Full article

Understanding dry-out-induced weakening of reservoir and caprock rocks driven by gas displacement is critical for ensuring the operational safety and efficiency of underground gas storage (UGS). Using core samples from the Xiangguosi UGS collected from different regions and stratigraphic intervals, we quantify the evolution of dynamic elastic parameters during simulated downhole dry-out with a joint ultrasonic and nuclear magnetic resonance (NMR) monitoring system. The results show that as water saturation (S_w) decreases, the dynamic bulk modulus (K_d) and P-wave velocity (V_p) decline by varying degrees across specimens, with reductions ranging from 3.0% to 50.48% and from 1.34% to 17.56%, respectively, whereas the dynamic shear modulus (G_d) and S-wave velocity (V_s) show only minor variations throughout the process. These findings demonstrate that the sensitivity of dynamic parameters to dry-out is strongly specimen-dependent. Further analysis indicates that the dry-out response is highly variable and depends on a combination of petrophysical properties. Among these, the heterogeneity of the initial pore structure acts as an important factor, with its influence shaped by mineralogy and bulk frame rigidity. Cores with multimodal pore size distributions and well-developed macropores (long T₂ components) respond more strongly to dry-out, whereas higher clay mineral contents tend to mitigate modulus degradation by retaining water under stronger capillary confinement. Based on these observations, we propose a conceptual model of pore support and skeleton constraint. The model suggests that dry-out weakening arises from a progressive loss of pore fluid volumetric support to the rock skeleton as free water is preferentially displaced from meso- and macropores. These findings provide key experimental evidence and mechanistic insights for using geophysical methods to monitor dry-out zone expansion and to assess long-term formation stability in UGS. Full article

Accurate prediction of subsurface temperature distributions is essential for geothermal reservoir assessment, thermal performance evaluation, and decision support in reservoir management. However, repeated high-resolution numerical simulations are computationally expensive, particularly when multiple scenarios, heterogeneous petrophysical fields, and varying grid resolutions must be analyzed. This study presents a U-Net-based surrogate modeling framework for fast geothermal temperature field prediction on structured grids, coupled with interpolation strategies for handling unseen grid resolutions and intermediate time instances. Training and evaluation data are generated using the MATLAB Reservoir Simulation Toolbox (MRST) (24.1.0.2578822 (R2024a) Update 2) under multiple porosity–permeability realizations and at several grid resolutions (130 × 73, 67 × 37, 36 × 19, and 20 × 11) on a 2D grid. Data preprocessing and reshaping techniques are used to preserve spatial correspondence across resolutions. For fixed trained grids, the surrogate directly predicts temperature fields from porosity, permeability, and time inputs. For unseen grids, a grid interpolation strategy combines predictions from neighboring trained resolutions using weighted blending based on target grid cell count, followed by spatial resizing to the requested resolution. In addition, time interpolation is used to estimate temperature maps at intermediate time steps between predicted/simulated snapshots. The proposed framework enables rapid generation of temperature maps while maintaining spatial structure, making it suitable for efficient geothermal screening and multiscale scenario analysis. Full article

Electrical resistivity tomography (ERT) serves as an auxiliary tool for marine engineering geological investigation. Through modeling, the effectiveness of this method was evaluated in areas affected by hydrological and underwater environmental changes, with a focus on the submarine geological structure in nearshore environments. The effects of pore water mineralization and cation exchange capacity on the resistivity of seabed sedimentary layers were investigated via rock physics modeling, and the corresponding relationship curves were obtained. Physical simulation experiments were also conducted to validate the rock physics modeling results. This process quantitatively analyzed the factors influencing the resistivity of nearshore seabed sediments, obtained the resistivity of each sedimentary layer, and interpreted the causes of resistivity variations. Resistivity models of different terrains were established for sandy clay seabed sediments with varying water salinities. The innovative use of submarine electrical resistivity tomography was proposed, and its feasibility and advantages were confirmed through numerical simulations. Field tests along the Baltic Sea coast demonstrated that, compared with previous methods, submarine electrical resistivity tomography offers higher resolution and improved exploration performance. Full article

Gallium (Ga) in coal is a nationally emerging strategic mineral resource, yet research on using petrophysical methods to detect the spatial variation in critical metals in coal seams remains limited. Analyzing the distribution characteristics of Ga-rich coal using geophysical well-logging methods is of great significance for the development and utilization of Ga. This study introduces a quantitative method for predicting Ga-rich laminations in ultra-thick bituminous coal seams by integrating: (i) wireline-log-based lithofacies classification, (ii) lithofacies-constrained mineral inversion, and (iii) lithofacies-constrained and laboratory-established Ga–mineral correlations. The coal seam was first classified into four distinct lithofacies types—(i) parting, (ii) medium-ash coal (MA), (iii) low-ash coal (LA), and (iv) extra-low-ash coal (ELA)—through integration of conventional wireline log interpretation, cluster analysis, and XGBoost machine learning. Second, lithofacies-constrained Ga–host mineral associations were established by integrating core sample analysis, correlation analysis, and linear regression modeling. Third, mineral content predictions for each lithofacies were obtained through wireline-log-based mineral inversion, constrained by petrophysical boundaries. Finally, prediction uncertainties were evaluated using Markov Chain Monte Carlo (MCMC) simulation, while Ga-rich laminations were predicted by integrating log-derived mineral inversion results with regressed Ga prediction models. The results demonstrate strong agreement between mineral inversion and XRD analyses within uncertainty ranges, achieving a prediction accuracy of 73.6% for Ga. This validated methodology presents a novel approach for quantifying Ga concentrations in coal, as demonstrated through a case study. Full article

Tight oil resources are a critical component of China’s energy strategy, with significant potential in basins such as the Songliao Basin, particularly within the Fuyu oil layer. However, tight sandstone reservoirs, characterized by low porosity and permeability, present substantial challenges for exploration and development. Accurate reservoir classification and characterization are therefore essential for optimizing exploration efforts and resource management. This study investigates the characterization and classification of tight sandstone reservoirs in the Fuyu oil layer of the Songliao Basin, focusing on their impact on crude oil flow behavior. The research employs a variety of experimental methods, including high-pressure mercury intrusion (HPMI), nuclear magnetic resonance (NMR), and centrifugation tests, to analyze pore characteristics, fluid mobility, and reservoir physical properties. A unified classification framework is proposed, which integrates geological, petrophysical, and fluid flow perspectives. The reservoirs are categorized into four types based on porosity, permeability, and mercury intrusion curve characteristics. This classification provides valuable insights into reservoir quality, thereby aiding exploration and development decisions for tight oil resources in the Songliao Basin. Full article

Medium-deep tight sandstone reservoirs represent a new frontier for hydrocarbon exploration. Great natural gas exploration breakthroughs have been made in the third member of the Lingshui Formation in the Baodao Sag, Qiongdongnan Basin. However, the characteristics of tight sandstone reservoirs and the controlling factors of sweet spots remain poorly understood. Using thin sections, SEM and petrophysical data, this study analyzes reservoir properties and key factors controlling sweet-spot formation, and establishes a pore evolution model. The results show that the reservoirs are dominated by lithic feldspathic quartz sandstones, with feldspar dissolution pores, moldic pores and intergranular pores as major pore types, with average areal porosities of 3.90%, 3.57%, and 1.31%, respectively. Feldspathic quartz sandstones constitute sweet-spot reservoirs. The average porosity is 10.92%, and the average permeability is 6.73 × 10⁻³ μm². Grain size shows a positive correlation with reservoir quality. Compaction provides the basis for reservoir densification, resulting in a porosity loss rate of 22.0–28.0%, with an average of 24.0%. Dissolution is critical for sweet-spot development, forming secondary pore zones at 3800–3950 m and 4100–4400 m, with the dissolution-induced porosity increment ranging from 5.77% to 8.68% and averaging 7.20%. Late carbonate cementation further enhances reservoir densification, corresponding to a porosity loss rate of 5.70–10.9% with an average of 8.28%. This study provides a theoretical basis for sweet-spot evaluation and hydrocarbon exploration in deep-water areas of the South China Sea. Full article