Global tight-oil reserves are abundant, but the depletion development of numerous tight-oil reservoirs remains unsatisfactory. CO₂ injection development represents a significant method of reservoir production, potentially facilitating enhanced oil recovery (EOR) alongside CO₂ storage. Currently, limited research exists on advanced CO₂ injection and well pattern adjustment aimed at improving the oil recovery and CO₂ storage within tight-oil reservoirs. This paper focuses on the examination of tight oil within the Ordos Basin. Through the employment of slim-tube experiments, long-core displacement experiments, and reservoir numerical simulations, the near-miscible pressure range and minimum miscible pressure (MMP) for the target block were ascertained. The viability of EOR and CO₂ sequestration via advanced CO₂ injection was elucidated, establishing well pattern adjustment methodologies to ameliorate CO₂ storage and enhance oil recovery. Simultaneously, the impacts of the injection volume and bottom-hole pressure on the development of advanced CO₂ injection were explored in further detail. The experimental results indicate that the near-miscible pressure range of the CO₂–crude oil in the study area is from 15.33 to 18.47 MPa, with an MMP of 18.47 MPa, achievable under reservoir pressure conditions. Compared to continuous CO₂ injection, advanced CO₂ injection can more effectively facilitate EOR and achieve CO₂ sequestration, with the recovery and CO₂ sequestration rates increasing by 4.83% and 2.29%, respectively. Through numerical simulation, the optimal injection volume for advanced CO₂ injection was determined to be 0.04 PV, and the most favorable bottom-hole flowing pressure was identified as 10 MPa. By transitioning from a square well pattern to either a five-point well pattern or a row well pattern, the CO₂ storage ratio significantly improved, and the gas–oil ratio of the production wells also decreased. Well pattern adjustment effectively supplements the formation energy, extends the stable production lives of production wells, and increases both the sweep efficiency and oil recovery. This study provides theoretical support and serves as a reference for CO₂ injection development in tight-oil reservoirs.

In this study, a coupled thermo-hydro-mechanical model to simulate multiple hydraulic fracture propagation is presented. Fracture propagation with elastic deformation is described by using a displacement discontinuity method. The temperature distribution and induced thermal stress are calculated via a semi-analytical method in an explicit way. An iterative scheme is proposed to solve the coupling between fracture propagation with fluid flow and induced thermal stress. The numerical model is validated against related analytical solutions. Several numerical cases are modeled to investigate the controlling factors for uniform growth of multiple fractures. Results show that using non-uniform fracture spacings and proper increasing the spacing for fractures away from the heel of wellbore promote the uniform growth of multiple fractures by comparison with using uniform fracture spacings. Increasing the perforation diameter for the middle cluster also works. Besides, single-wing fracturing could greatly improve the uniform growth of multiple hydraulic fractures. Finally, it shows that the thermal stress has a significant influence on fracture geometrical size but has limited effect on fracture propagation path. In addition, the thermal effect promotes the uniform growth of multiple fractures.

Thin-interbedded low-permeability sandstone reservoirs are characterized by frequent sand–mudstone alternations and strong vertical heterogeneity, which make accurate sweet-spot identification and reliable development-performance prediction difficult. Conventional sweet-spot evaluation methods commonly rely on fixed weighting or linear parameter superposition, and thus cannot fully represent the interlayer flow imbalance and cross-layer stress barriers that govern thin-interbedded reservoirs. Supervised data-driven models can capture nonlinear relationships, but their application is limited when reliable sweet-spot labels are scarce. This study proposes a physics-constrained adaptive weight-optimization strategy based on an ANFIS–VAE dual-pathway network to establish an integrated sweet-spot evaluation system from the dimensions of production potential and fracturing potential. Two thin-interbedded-specific indicators are introduced. Permeability contrast quantifies interlayer petrophysical heterogeneity, and interlayer stress difference characterizes cross-layer fracture-propagation constraints. The optimized sweet-spot favorability index (SFI) is classified into three tiers using K-means++ clustering. Results show that oil saturation is the leading control on production potential, with a weight of 0.3052, while permeability contrast contributes approximately 20%. Interlayer stress difference dominates fracturing-potential evaluation, with a weight of 0.2534. Class I, Class II, and Class III sweet spots account for approximately 22%, 45%, and 33% of the study area, respectively. Compared with the conventional method, the proposed approach reduces the RMSE from 0.35 to 0.06 on a held-out well excluded from model training. Reservoir numerical simulation further confirms the geological rationality of the classification. Class I zones exhibit relatively uniform depletion with an effective recovery of approximately 65%, Class II zones show interlayer-differentiated depletion with an effective recovery of approximately 52%, and Class III zones display channelized flow under mudstone shielding with recovery below 40%. The proposed framework provides a physically consistent basis for sweet-spot grading, differentiated stimulation design, and zone-specific development deployment in thin-interbedded reservoirs.