A bottom water reservoir is universal in all reservoirs in the world. In the exploitation process of the bottom water reservoir, because the reservoir is in complete contact with bottom water, the natural energy supply of the bottom water reservoir is sufficient. At the same time, in the production process, the pressure drop generated by the formation is mainly concentrated near the wellbore, which leads to a short period of waterless oil production, fast water breakthrough, and fast water cut rise, which seriously affects the overall recovery factor and increases the risk of oil filed exploitation. Since the distribution of an interlayer enhances the heterogeneity of the reservoir, it has a prominent impact on the flow of oil and water in the bottom water reservoir. However, people know little about the impact of the interlayer on the bottom water reservoir. In this paper, the mathematical model of two-phase flow in the bottom water reservoir with the interlayer is proposed, and the numerical solution of the model is obtained by a finite element method. The influence of the distribution of the interlayer on the water cut rising law of the bottom water reservoir is analyzed. The results show that the bottom water is blocked by the interlayer and its own gravity and the rising height of the bottom water is limited, so that the interlayer has a significant inhibitory effect on the coning of the bottom water. The closer the interlayer is to the oil-water interface, the faster the water cut will rise; the narrower the interlayer is, the faster the bottom water ridge will advance; when the width of the interlayer is the same as that of the reservoir, the water cone will not appear; the higher the permeability of the interlayer is, the faster the upper body of the water cut will be; when the permeability of the reservoir and the interlayer is over 1000, the influence of the interlayer on the water cut rise is not obvious; the thickness of the interlayer on the water cut rise law has little effect. Finally, through the case analysis, it is proposed that the new horizontal wells should be arranged in the position where the interlayer develops. The findings of this study can help for the better understanding of control laws of the interlayer on the bottom water and providing a crucial theoretical basis for the development of the bottom water reservoir.

Metal–organic frameworks (MOFs) typically exist in the form of powders or dispersed crystals, which limits their direct application in practical engineering scenarios that require monolithic structures and processability. To address this issue, the present study successfully anchored MOF (zeolitic imidazolate framework-8, ZIF-8) nanocrystals within a porous silicon carbide (p-SiC) substrate via a facile in situ growth strategy, achieving both stable macroscopic loading and intimate microscopic interfacial bonding. The resulting ZIF-8/p-SiC composite exhibits a hierarchical porous structure, with a specific surface area approximately 183 times higher than that of the raw p-SiC, alongside a substantially enhanced CO₂ adsorption capacity. By utilizing a low-cost p-SiC support and mild ZIF-8 synthesis conditions, this work demonstrates excellent reproducibility and scalability, providing a facile and effective pathway for fabricating MOF/porous media composite systems that possess both superior mechanical properties and tailored pore structures. Additionally, the developed MOF/p-SiC composites can serve as controllable rock-analog porous media, offering new perspectives for investigating MOF-rock interfacial interactions and CO₂ geological sequestration mechanisms, thereby establishing an organic link between fundamental materials science and geological engineering applications.

In this paper, a new rate decline analysis model of horizontal wells with variable conductivity and uneven distribution of multiple fractures is proposed. By Laplace transformation, point source integration, and superposition principle, solutions of multiple infinite conductivity fractures in closed reservoirs are obtained. By coupling Fredholm integral equation of variable conductivity, linear equations of variable conductivity fractures in Laplace space are obtained. Gauss-Newton iteration, Duhamel convolution, and Stehfest numerical inversion method are used to obtain the bottom hole production solution. The accuracy of the results is verified by comparing with Eclipse software simulation. Then, the influence of some important reservoir and fracture parameters on the production is analyzed. The calculative results show that the smaller the fracture spacing is, the earlier the fracture begins to decline, the more the production will decrease; the change of different fracture length with the total fracture length unchanged has almost no effect on the production; the angle between fracture and -axis has an important effect on the production; the smaller the angle between fracture and -axis is, the stronger the interference between fractures is, the higher the production; the initial fracture conductivity affects the early production behavior, and the higher the initial fracture conductivity, the higher the production; the larger the fracture declines index, the lower the production, but the decreasing range gradually decreases with the increase of the decline index; the larger the reservoir drainage radius, the later the energy depletion stage, the higher the production. At last, a good fitting effect is obtained by fitting an example of oil field. The model proposed in this paper enriches the model base of rate decline analysis of fractured horizontal wells and lays a theoretical foundation for efficient development and practice of tight reservoirs.

In the process of stimulated reservoir volume of tight reservoir, horizontal well can form three zones, the inner zone is multistage fracturing zone, the middle zone is skin damage zone, and the outer zone is undamaged zone. In this paper, a transient well test analysis model of multistage fracturing horizontal well in three area composite reservoir is proposed. Based on Laplace transformation, point source integration, and superposition principle, the infinite conductivity multifracture model of three area composite reservoir is obtained. The linear equations of finite conductivity multifracture in Laplace space are established by using the equal conditions of flow and pressure at the fracture wall. Gauss-Newton iteration method and Stehfest number are used to obtain the solution of wellbore pressure. The accuracy of the results is verified by numerical simulation. Then, the flow characteristics of multistage fracturing horizontal wells in three area composite reservoirs are analyzed by type curves. The flow is divided into ten stages, which are the bilinear flow, the linear flow, the first radial flow stage, the inner zone linear flow, the inner zone radial flow, the middle zone linear flow, the middle zone radial flow, the outer zone linear flow, the outer zone radial flow, and the boundary dominated flow. The pressure derivative curves show different characteristics in different flow stages. The influences of fracture conductivity, fracture spacing, radius ratio of the middle zone to inner zone, radius ratio of the outer zone to the middle zone, permeability ratio of inner zone to the middle zone, permeability ratio of inner zone to outer zone, storage capacity ratio of inner zone to the middle zone, and storage capacity ratio of inner zone to outer zone on type curves are analyzed. Finally, the application and reliability of the proposed model are verified by a case example.

Strong heterogeneity and ambiguous seismic responses hinder reliable sandstone thickness prediction when using a single seismic attribute in the lower sandstone interval of the Talang Akar Formation (hereafter abbreviated as the LTAF interval) in the B gas field, South Sumatra Basin. To address this challenge, we propose a seismic attribute fusion and reservoir sweet-spot prediction framework based on a multiscale convolutional neural network (CNN) integrated with a self-attention module. Multiple seismic attribute volumes are organized as multi-channel 2D attribute slices, and parallel convolutions with kernel sizes of 3 × 3, 5 × 5, and 7 × 7 are employed to capture spatial features ranging from thin-bed boundaries and channel morphology to sand-body assemblage distribution. The self-attention module explicitly models inter-attribute dependencies and performs adaptive weighted fusion to suppress noise and emphasize informative attributes. The network adopts a dual-output design, producing (i) a sandstone thickness prediction map at the same spatial resolution as the input and (ii) attribute importance scores for quantitative attribute selection and geological interpretation. Using 3D seismic data and well-constrained thickness labels, the proposed model achieves an R² of 0.8954, outperforming linear regression (R² = 0.8281) and random forest regression (R² ≈ 0.8453). The learned importance scores indicate that amplitude-related attributes (e.g., RMS amplitude and maximum amplitude) contribute most to thickness prediction, whereas frequency- and energy-related attributes show relatively lower contributions, which is consistent with bandwidth-limited resolution effects. Overall, the proposed framework unifies attribute fusion, thickness prediction, and interpretability within a single model, providing practical support for fine reservoir characterization and development optimization in heterogeneous sandstone reservoirs.