Search Results (84)

Total organic carbon (TOC) is a key parameter for geological sweet spot optimization and resource evaluation. However, accurate TOC prediction remains challenging under small-sample conditions because conventional physical and machine learning methods are commonly limited by insufficient labeled data. To address this problem, this study proposes a hybrid deep learning framework that integrates a convolutional autoencoder with a BP neural network (CAE-BPNN). In this framework, the CAE is first used to learn representative feature expressions from abundant unlabeled logging data, and the learned encoder is then transferred to the supervised prediction stage, where labeled samples are used for TOC prediction through the BPNN. The dataset includes 177 measured TOC samples and 1388 unlabeled logging samples from the Fengcheng Formation shale in Well MY1, in the Mahu Sag, and data from Well MY2 are used for independent validation. Model performance is evaluated using five-fold cross-validation with the coefficient of determination (R²) and root mean square error (RMSE) as metrics. For Well MY1, CAE-BPNN achieves the best performance, with R² = 0.89 and RMSE = 0.061, outperforming CNN (R² = 0.85, RMSE = 0.075), GBDT (R² = 0.83, RMSE = 0.076), RF (R² = 0.81, RMSE = 0.082), and BPNN (R² = 0.77, RMSE = 0.085). In the independent validation using Well MY2, CAE-BPNN also shows superior predictive performance, with R² = 0.81 and RMSE = 0.367. These results indicate that unlabeled logging data can effectively enhance feature representation and improve TOC prediction accuracy under limited labeled-sample conditions. The proposed method provides an effective solution for small-sample TOC prediction and offers a reliable basis for movable oil evaluation using the oil saturation index (OSI), as well as a reference for predicting other geological parameters such as S1, S2, and porosity. Full article

Tight oil horizontal wells in the Mahu block of the Junggar Basin commonly show rapid production decline and limited target-domain samples. These characteristics make accurate production prediction difficult. This work aims to address the small-sample overfitting problem of tight oil horizontal well production prediction in Mahu Sag with rapid production decline and limited measured well data. The concept of transfer learning is introduced to address the issue of insufficient target domain samples, and the Pearson correlation coefficient is utilized to select the main controlling factors for production from the production data. Next, based on the features extracted by the temporal convolutional network at different data scales, a multi-head attention mechanism is introduced to capture the dependencies across different time steps. Subsequently, an improved sparrow search algorithm is employed to optimize the hyperparameters of the bidirectional long short-term memory network. Finally, the bidirectional long short-term memory network is integrated to further extract the nonlinear features learned by the temporal convolutional network to conduct production prediction. Tailored to the exploitation conditions of tight oil horizontal wells in this block, a tight oil production prediction model based on transfer learning and the multi-head attention mechanism is proposed. Experimental results demonstrate that, compared with the standard bidirectional long short-term memory network, the proposed model’s evaluation metrics show a 60.93% decrease in root mean square error, a 78.53% decrease in mean absolute percentage error, and a 43.68% increase in coefficient of determination. This verifies the effectiveness of transfer learning in solving small-sample modeling challenges, providing precise technical support for the optimization of tight oil fracturing parameters and stimulation treatments in the Mahu block. The novelty of this work lies in the integration of multi-head attention temporal convolution network, quantum sparrow optimized bidirectional long short-term memory network and cross-block transfer learning for small-sample tight oil forecasting. Full article

The Fengcheng Formation in the Mahu Sag of the Junggar Basin represents one of the oldest and most significant alkaline lacustrine systems, hosting abundant dolomite that serves as a key unconventional reservoir. However, the formation mechanism of dolomite remains unclear. This study integrates detailed petrography, geochemistry and cyclostratigraphy to elucidate the origin and distribution of dolomite. Petrographic characteristics indicate a penecontemporaneous origin for the dolomite, with no apparent hydrothermal influence. Mineralogical features exhibit a multi-zonation structure of dolomite, aligning with in situ Fe content, jointly indicating that a multi-stage formation process of dolomite from core to rim. Microbial methanogenesis likely played an important role in the dolomite formation. Spatially, dolomite is enriched in the transition zone but scarce in the depocenter zone, where sodium carbonate prevails. This distribution is primarily controlled by pH differentiation between the transition zone and the depocenter zone of the Mahu Sag. In the transition zone, orbitally driven wet–dry cycles regulated the lake-level change, which, in turn, controlled pH fluctuation, as revealed by the silica precipitation during humid phases and dissolution during arid intervals. In the depocenter zone, lake water remained at a high-pH state, which was unfavorable for dolomite formation. These findings highlight that pH dynamics, linked to orbital climate cycles, played a critical role in governing dolomite formation and distribution in this ancient alkaline lake, providing new insights for the formation of dolomite in alkaline lacustrine environments. Full article

The Lower Permian Fengcheng Formation (P₁f) in the Mahu Sag, Junggar Basin, records an uncommon alkaline–lacustrine hybrid system where siliciclastic, volcaniclastic inputs, and endogenous carbonates jointly build strong reservoir heterogeneity. This study clarifies how depositional framework architecture and diagenetic evolution jointly control effective pore–throat connectivity and reservoir effectiveness. We examined 55 core samples from nine wells using X-ray diffraction (XRD), scanning electron microscopy (SEM), low-pressure N₂ adsorption (LPNA), high-pressure mercury intrusion (HPMI), and nuclear magnetic resonance (NMR) T₂ spectra, and identified five lithofacies: siliciclastic-dominated (SDF), volcaniclastic (VTF), mixed siliciclastic–carbonate (MSCF), carbonate-dominated (CDF), and alkaline mineral-rich (AMF). Reservoir quality is strongly lithofacies-dependent and cannot be inferred from pore volume alone. The SDF and CDF are both dominated by the >200 nm domain, but only the SDF preserves a coarse pore–throat framework that sustains effective flow; the MSCF is characterized by a stronger 10–50 nm contribution and a more tortuous network, and the VTF by enrichment of the 50–200 nm domain. In the SDF, quartz is preferentially associated with the >200 nm domain and dolomite with the 50–200 nm domain, consistent with coarse residual pores preserved by rigid grains and intercrystalline or dissolution-related pores, respectively. The AMF should be treated as two subtypes: the Na-borosilicate subtype shows high >200 nm volume but very high tortuosity, whereas the Na-carbonate subtype shows co-development of the 10–50 nm and >200 nm domains with lower threshold pressure and tortuosity, indicating better pore-body–throat matching and more favorable reservoir behavior. These findings provide a lithofacies-based framework for screening effective reservoir intervals in alkaline lacustrine hybrid systems. Full article

The Mahu Sag, a hydrocarbon-rich depression within the Junggar Basin, hosts significant petroleum resources. Here, the Permian Fengcheng Formation shale oil reservoirs have emerged as a primary exploration target. This study investigates fracture development within these alkaline lacustrine shales, a critical factor governing hydrocarbon migration and accumulation. Through integrated petrographic and geochemical analyses, we elucidate a multifactorial fracture formation mechanism driven by the interplay of alkaline minerals, stress, and fluids. Two distinct fracture types were identified: bedding-complex fracture veins (BCFVs) and Y-shaped high-angle fracture veins (Y-HFVs). Both fracture types result from alkaline fluid–rock interactions, which induce fracture opening along specific orientations, alter fracture angles, and control aperture width and final morphology. Alkaline mineral assemblages further influence fracture evolution via dissolution–precipitation cycles. Concurrently, these assemblages preserve hydrocarbons by inhibiting the thermal maturation of organic matter, as evidenced by variations in fluid inclusion fluorescence. The fracture networks act as crucial migration pathways, with the BCFV containing higher-maturity hydrocarbons (indicated by blue-green fluorescence) and the Y-HFV retaining less mature fluids (indicated by yellow-green fluorescence). This study presents the first systematic characterization of the multifactorial controls on fractures in alkaline lake environments, proposing a cooperative “alkaline minerals–stress–fluids” mechanism. These findings provide a new framework for understanding fracture development in alkaline lacustrine shales and offer valuable insights for shale oil exploration in analogous depositional settings. Full article

Highly deviated wells commonly exhibit large errors in horizon calibration because the logging path follows an inclined borehole trajectory, whereas post-stack seismic processing effectively treats wave propagation as vertical. This mismatch has received limited attention. Here, we performed horizon calibration and velocity-model building for highly deviated wells drilled in the Mahu Sag, Junggar Basin, and obtained three key findings. First, the assumed vertical travel path in post-stack data is the primary cause of the initial mis-tie for highly deviated wells. Second, calibration in the deviated interval requires a strategy distinct from that of vertical wells and may involve substantial stretching or squeezing of the original logs to achieve a consistent time-depth relationship. Third, the map-view projection of a highly deviated well is essentially linear; relative to vertical wells, it provides denser in situ velocity constraints and, with pseudo-well control, supplies 2D velocity information along the well-trajectory plane, thereby improving velocity-field modeling. Validation against drilling data showed that this workflow improved well ties and refined the velocity model, providing practical guidance for geological well planning and reducing drilling risk. Full article

Tight oil reservoirs developed by volume fracturing commonly suffer from insufficient energy replenishment and rapid production decline. Although CO₂ huff-n-puff can enhance oil recovery, it is prone to early gas channeling through fracture-dominated high-permeability channels, and its effectiveness decreases with successive cycles. To clarify the coupled effects of fracture morphology and foam on CO₂ huff-n-puff performance, comparative experiments of multi-cycle CO₂ huff-n-puff and foam-assisted CO₂ huff-n-puff were conducted on fractured tight cores from the Xinjiang Mahu reservoir, combined with offline low-field NMR T₂ analysis. The results show a clear first-cycle dominant effect, and better reservoir properties lead to higher initial recovery and slower decline in subsequent cycles. Cross fractures increase the final oil recovery by 81.1%, 83.4%, and 73.2% for the three reservoir types, respectively, whereas excessively large fracture apertures reduce recovery because of intensified gas channeling. Foam further improves oil recovery, with 0.6% giving the optimum performance and increasing final recovery by 20.11%, 14.79%, and 8.36% in Type-I, Type-II, and Type-III reservoirs, respectively. NMR results indicate that foam mainly enhances the mobilization of remaining oil in medium and large pore–throat systems by blocking preferential flow channels and enlarging the effective swept volume. This study provides an experimental basis for parameter optimization and mechanistic understanding of foam-assisted CO2 huff-n-puff in fractured tight reservoirs. Full article

Multi-stage multi-cluster hydraulic fracturing in conglomerate reservoirs is often characterized by strong cluster-to-cluster variability in fluid distribution, which can reduce stimulation efficiency. However, field-scale observations that constrain how injected fluid is partitioned among clusters remain limited, especially in strongly heterogeneous formations. In this study, wide-field electromagnetic (WFEM) monitoring was applied to a horizontal well completed in the Baikouquan Formation sandstone–conglomerate reservoir of the Mahu Sag, Junggar Basin. The monitored treatment consisted of 13 fracturing stages, each containing six perforation clusters. Time-lapse electromagnetic data acquired during pumping were inverted to reconstruct the spatiotemporal evolution of the effective conductive fluid-swept region. Based on the inversion results, we introduce a set of quantitative proxy indicators (swept area, swept length, cluster-specific sweep, and an asymmetric index) to support relative comparison of fluid distribution patterns at both stage and cluster scales. Results show pronounced non-uniformity within and between stages, even under similar pumping conditions. A limited number of clusters exhibit stronger and farther-reaching WFEM-inferred conductive-fluid responses, whereas other clusters show weaker or more localized responses. Asymmetric sweep patterns on opposite sides of the wellbore are also commonly observed. These patterns are consistent with the combined influences of reservoir heterogeneity, local structural/stress disturbances, and operational factors, although WFEM alone does not uniquely validate causal mechanisms of fracture growth. Overall, this study demonstrates that WFEM monitoring provides a field-scale proxy tool for delineating effective conductive fluid-swept regions and for evaluating cluster-to-cluster variability under consistent acquisition and inversion settings. The findings offer practical guidance for interpreting fluid distribution and optimizing multi-cluster fracturing in strongly heterogeneous unconventional reservoirs. Full article

Low-voltage mini-grids play a crucial role in expanding electricity access for rural and remote communities. However, they continue to face technical and operational barriers that hinder their performance and reliability. This study reviewed the evolution of research on technical challenges in low-voltage mini-grids from 2005 to 2025. Using the PRISMA approach, data were extracted from the Scopus database, yielding 155 publications for bibliometric analysis. Bibliometrix in R Studio was used to examine publication trends, geographical contributions, and thematic evolution, while qualitative synthesis identified key engineering and operational constraints. The findings revealed a steady increase in research outputs since 2020, driven by global policy commitments, including Sustainable Development Goal 7 and the Paris Agreement. Persistent technical barriers include voltage and frequency instability, inadequate power quality monitoring, inefficient integration of energy storage, poor control coordination, and limited system design optimisation. African nations contribute less to global research despite being most affected by energy poverty, highlighting capacity and funding gaps. The study highlights the need for integrated solutions combining smart control, hybrid storage, and grid-interconnection technologies to enhance resilience and reliability. For policymakers and practitioners, the findings advocate for investment in research, capacity building, and locally tailored technical standards designed for resource-constrained contexts. This review provides a comprehensive evidence base to guide future research and policy directions aimed at achieving sustainable, technically robust, and financially viable mini-grid systems for universal energy access. Full article

Efficient proppant transport in conglomerate reservoirs is severely constrained by rough fracture surfaces and strong geometric heterogeneity, leading to premature near-wellbore deposition and insufficient distal support. To address this challenge, this study aims to clarify the transport and deposition mechanisms of proppants in rough-wall fractures representative of the Mahu conglomerate reservoir. A large-scale visualized physical simulation system with an artificial rough fracture (20 m length × 4.5 m height) was developed based on dynamic similarity principles, enabling long-distance proppant transport observation under controlled pumping rate, fluid viscosity, proppant size, and sand concentration. Ten systematic experiments were conducted, and real-time particle motion and sand ridge evolution were captured using high-speed imaging and pressure monitoring. The results show that proppants form longitudinally layered sand ridges that evolve through three stages: leading-edge initiation, equilibrium-height growth, and distal extension. Viscosity and sand concentration primarily control propped-area continuity, while pumping rate governs transport distance and particle size affects structural stability. Rough fracture surfaces significantly intensify near-wellbore accumulation by enhancing energy dissipation and local flow heterogeneity. These findings provide mechanistic insights into proppant transport in rough fractures and offer quantitative guidance for optimizing fracturing parameters in conglomerate reservoirs. Full article

Shale pores and throats are key factors controlling the enrichment and development efficiency of shale oil and gas. However, the characteristics and formation mechanisms of shale pores and throats remain unclear. Taking the Permian continental shales in the Mahu Sag of the Junggar Basin as an example, this paper studies the formation mechanisms of pores and throats in shales of different lithofacies through a series of experiments, such as high-pressure mercury injection and scanning electron microscopy. The results show that the Permian continental shales in the Junggar Basin are mainly composed of five lithofacies: rich siliceous shale (RSS), calcareous–siliceous shale (CSS), argillaceous–siliceous shale (ASS), siliceous–calcareous shale (SCS), and mixed-composition shale (MCS). The pores in shale are dominated by intergranular and intragranular pores. The intergranular pores are mainly primary pores and secondary dissolution pores. The primary pores are mainly slit-like and polygonal, with diameters between 40 and 1000 nm. The secondary dissolution pores formed by dissolution are irregular with serrated edges, and their diameters range from 0.1 to 10 μm. The throats are mainly pore-constriction throats and knot-like throats, with few vessel-like throats, overall exhibiting characteristics of nanometer-scale width. The mineral composition has a significant influence on the development of pores and throats. Siliceous minerals promote the development of macropores, and carbonate minerals promote the development of mesopores. Clay minerals inhibit pore development. Diagenesis regulates the development of pores and throats through mechanical compaction, cementation, and dissolution. Compaction leads to a reduction in porosity, and cementation has varying effects on the preservation of pores and throats. Dissolution is the main factor for increased pores and throats. These findings provide a lithofacies-based geological framework for evaluating effective porosity, seepage capacity, and shale oil development potential in continental shale reservoirs. Full article

To address the challenges of strong heterogeneity and poor crude oil mobility in tight conglomerate reservoirs of the Mahu Oilfield, this study systematically evaluated the effects of different surfactants on wettability alteration, spontaneous imbibition, and relative permeability through high-temperature/high-pressure spontaneous imbibition experiments, online Nuclear Magnetic Resonance (NMR) monitoring, and relative permeability measurements. Core samples from the Jinlong and Madong areas (porosity: 5.98–17.55%; permeability: 0.005–0.148 mD) were characterized alongside X-Ray Diffraction (XRD) data (clay mineral content: 22–35.7%) to compare the performance of anionic, cationic, nonionic, and biosurfactants. The results indicated that the nonionic surfactant AEO-2 (Fatty Alcohol Polyoxyethylene Ether) (0.2% concentration) at 80 °C exhibited optimal performance, achieving the following results: 1. a reduction in wettability contact angles by 80–90° (transitioning from oil-wet to water-wet); 2. a decrease in interfacial tension to 0.64 mN/m; 3. an imbibition recovery rate of 40.14%—5 to 10 percentage points higher than conventional fracturing fluids. NMR data revealed that nanopores (<50 nm) contributed 75.36% of the total recovery, serving as the primary channels for oil mobilization. Relative permeability tests confirmed that AEO-2 reduced residual oil saturation by 6.21–6.38%, significantly improving fluid flow in highly heterogeneous reservoirs. Mechanistic analysis highlighted that the synergy between wettability reversal and interfacial tension reduction was the key driver of recovery enhancement. This study provides a theoretical foundation and practical solutions for the efficient development of tight conglomerate reservoirs. Full article

This study investigates the effects of CO₂–water–rock interactions on shale oil reservoirs, specifically focusing on the mineral dissolution and pore structure alterations in shale samples from the second section of the Permian Fengcheng Formation in the Mahu Depression, Junggar Basin. Core soaking experiments were conducted under high-temperature and high-pressure conditions to simulate reservoir environments. Mineral evolution, ion migration, and microstructural changes were qualitatively and quantitatively analyzed using X-ray Diffraction (XRD), Inductively Coupled Plasma (ICP) spectroscopy, and Scanning Electron Microscopy (SEM). The findings indicate that CO₂-induced mineral dissolution follows a distinct sequence: calcite > dolomite > potassium feldspar > sodium feldspar, which is directly reflected in the concentration of ions (Ca²⁺ > Mg²⁺ > K⁺ > Na⁺) in the solution. The dissolution rate and pore structure enhancement are significantly influenced by lamina density, with dolomitic rocks with high lamina density showing greater dissolution and porosity increase, and the lamina area greater than the matrix area. This study demonstrates that the dynamic changes of rock minerals are the core mechanism for controlling the pore structure of reservoirs, showing how CO₂–water–rock reaction enhances the porosity and connectivity of shale reservoirs, thereby improving oil recovery potential. Full article

This study investigates the mechanisms behind strong water sensitivity in some low-clay-mineral-content tight conglomerate reservoirs in China’s Mahu Sag. Using core-scale water sensitivity tests, mineral analysis, in situ micro-CT scanning, and digital core techniques, we analyzed how water sensitivity alters pore structures across cores of varying permeability. Key findings include the following: (1) Water sensitivity damage increases as initial gas permeability decreases. (2) Despite low clay content, significant water sensitivity arises from the combined effect of water and velocity sensitivity, driven mainly by illite and kaolinite concentrated in gravel-edge fractures and key flow channels. (3) Water sensitivity causes non-uniform pore structure changes—some macropores and throats enlarge locally, reflecting heterogeneity. (4) Structural responses differ by permeability: medium–low permeability cores suffer from clay mineral swelling and particle migration, whereas high-permeability cores resist overall damage and may even have main flow paths enhanced by flushing. (5) Water sensitivity mainly degrades smaller pores but can improve larger ones, with the critical pore-size threshold between macro- and micro-pores inversely related to permeability. This work clarifies the pore-scale mechanisms of water sensitivity in some low-clay-mineral-content tight conglomerates, and can provide guidance for the optimization of water types injected into similar conglomerate reservoirs. Full article

Ultra-deep shale in the Mahu Sag, characterized by difficult-to-drill formations, exhibits high resistivity. This study uses XRD and petrophysical testing on 12 dry core samples (depths 4600–5000 m) to characterize mineral composition and evaluate resistivity-influencing factors. Mineralogical analysis reveals that brittle minerals, dominated by quartz and feldspar (>50%), constitute the primary components of the ultra-deep shale in the Mahu Sag, with quartz, feldspar, and carbonates collectively accounting for ~80%. Clay (~6%) and pyrite (<5%) contents are notably low, resulting in elevated resistivities of 10⁵–10⁷ Ω·m. Resistivity correlates negatively with pyrite (r = −0.588) and feldspar (r = −0.319) but positively with dolomite (r = 0.209), quartz (r = 0.017), and porosity (r = 0.749). At elevated temperatures (100 °C), resistivity declines owing to enhanced ionic conduction. These findings clarify high-resistivity mechanisms, supporting resistivity-based drilling parameter optimization. Full article