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Addressing the issue of poor water injection development effectiveness caused by strong water sensitivity damage in the conglomerate reservoirs of the Xinjiang Oilfield, this paper carries out experimental research on CO2 displacement and CO2 huff-n-puff to improve oil recovery in reservoirs under the conditions of reservoirs (86 °C, 44 MPa) by using a high-temperature and high-pressure large physical modeling repulsion device based on the artificial large-scale physical modeling of conglomerate oil reservoirs in the Xinjiang oilfield. The results showed that at any displacement rate, CO2 displacement exhibits the trend where oil production initially increases and then decreases. The higher the gas injection rate, the higher the initial oil well production, and the shorter the time it takes for CO2 to break through to the bottom of the well. After a breakthrough, production declines more rapidly. The oil recovery rate varies with different gas injection rates, initially increasing and then decreasing as the injection rate changes. The highest oil recovery rate was observed at an injection rate of 1.5 mL/min (equivalent to 38 t/d in the field). The efficiency of CO2 displacement with multiple injection-production cycles is low; on the same scale of gas injection, single-cycle injection and production were more effective than multiple-cycle injection and production. CO2 huff-n-puff can improve oil recovery, with a higher CO2 injection pressure and a longer shut-in time leading to greater oil recovery. As the shut-in time increases, the efficiency of CO2 oil exchange also improves. The strong supply capacity of the large physical model results in a tendency for the oil production curves of multiple huff-n-puff cycles to converge.

Land use change detection (LUCD) is a critical technology with applications in various fields, including forest disturbance, cropland changes, and urban expansion. However, the current review articles on LUCD tend to be limited in scope, rendering a comprehensive review challenging due to the vast number of publications. This paper systematically reviewed 3512 articles retrieved from the Web of Science Core database between 1985 and 2022, utilizing a combination of bibliometric analysis and machine learning methods with LUCD as the main focus. The results indicated an exponential increase in the number of LUCD studies, indicating continued growth in this research field. Commonly used methods include classification-based, threshold-based, model-based, and deep learning-based change detection, with research themes encompassing forest logging and vegetation succession, urban landscape dynamics, and biodiversity conservation and management. To build an intelligent change detection system, researchers need to develop a flexible framework that integrates data preprocessing, feature extraction, land use type interpretation, and accuracy evaluation, given the continuous evolution and application of remote sensing data, deep learning, big data, and artificial intelligence.

Due to the unclear seepage mechanism for shale oil, it is hard to establish a reasonable mathematical model to describe the flowing law. In this study, a real shale pore structure was reconstructed with CT scanning and a numerical model of fluid flowing in the real shale pore is developed with COMSOL, based on the boundary slip at the micro-nano pore scale to study the causes of nonlinear seepage. A two-fluid model is employed to establish a simple mathematical model to describe the relationship between the flow rate and the pressure gradient using the effective slip length to account for the influence of pore structure and true slip, and the established model is verified with experimental data coming from Jiyang shale oil. The results indicated that the pore structure greatly affected the shape of the seepage curve. With the increase in displacement pressure, the percentage of fluid involved in the flow increased until it became stable, showing a changing trend from nonlinearity to linearity. The established model can fit the experimental data well and reasonably characterize the nonlinear seepage of shale oil.

With the application of new-generation information technology in the full life cycle process of a complex product, it is showing the characteristics of multi-source, real-time, heterogeneous, cross-domain transmission. Large data volume and low value density emerge in the process of complex product design manufacturing and services (DMS). This leads to “information islands” and insufficient utilization of cross-domain reliability data in the process of integration of DMS for complex product R&D design data, manufacturing data and operation and maintenance services (O&MS) data. This paper proposes and illustrates a framework of complex product DMS integration based on reliability data, including complex product design optimization based on manufacturing and service reliability data, complex product intelligent manufacturing process optimization based on real-time reliability data and complex product O&MS optimization based on multi-source heterogeneous reliability data. Additionally, it then realizes complex product design reliability and optimization, manufacturing process reliability and optimization and O&MS reliability and intelligent decision optimization based on reliability data. Finally, the DMS integration framework based on reliability-data-driven proposal is corrected through the case of engine MDS integration, which can effectively improve the cross-domain reliability data utilization and overall product reliability of complex products. The proposed framework extends the application of reliability theory in the process of complex product DMS integration and provides a reference for enterprises in the R&D, manufacturing and O&MS of complex products.

During the development of unconventional reservoirs with high sand production rate and fine silt content such as heavy oil and hydrate reservoirs, silt sand blockage problem is a serious issue. A two-stage gravel-packing sand control technique is applied to solve the silt sand blockage now. However, traditional experiments on this technique could not obtain the dynamic distribution law of intrusive sand in the gravel pack. In this study, a new visualization experiment based on hydrodynamic similarity criterion for studying particle blockage in gravel packs was conducted. Real-time monitoring of sand particle migration in the gravel pack could be achieved. Also, the stable penetration depth and the distributing disciplinarian of invaded particles could be determined. The results show that when the gravel-to-sand median size ratio of gravel bed I is less than five, the sand bridge can be formed at the front end of the gravel pack. This could prevent sand from further intruding. As the grain size of gravel bed II is increased, the flow velocity is reduced. Thus, the sand invading into gravel bed II tends to settle at the interface. A large amount of sand intrusion can happen to gravel pack II when the pore filling front breaks through the gravel bed I.

When the reservoir pressure is decreased lower than the dew point pressure in shale gas condensate reservoirs, condensate would be formed in the formation. Condensate accumulation severely reduces the commercial production of shale gas condensate reservoirs. Seeking ways to mitigate condensate in the formation and enhance both condensate and gas recovery in shale reservoirs has important significance. Very few related studies have been done. In this paper, both experimental and numerical studies were conducted to evaluate the performance of CO2 huff-n-puff to enhance the condensate recovery in shale reservoirs. Experimentally, CO2 huff-n-puff tests on shale core were conducted. A theoretical field scale simulation model was constructed. The effects of injection pressure, injection time, and soaking time on the efficiency of CO2 huff-n-puff were examined. Experimental results indicate that condensate recovery was enhanced to 30.36% after 5 cycles of CO2 huff-n-puff. In addition, simulation results indicate that the injection period and injection pressure should be optimized to ensure that the pressure of the main condensate region remains higher than the dew point pressure. The soaking process should be determined based on the injection pressure. This work may shed light on a better understanding of the CO2 huff-n-puff- enhanced oil recovery (EOR) strategy in shale gas condensate reservoirs.

Recently, the well-industry-production-scheme (WIPS) has attracted more and more attention to improve tight oil recovery. However, multi-well pressure interference (MWPI) induced by well-industry-production-scheme (WIPS) strongly challenges the traditional transient pressure analysis methods, which focus on single multi-fractured horizontal wells (SMFHWs) without MWPI. Therefore, a semi-analytical methodology for multiwell productivity index (MPI) was proposed to study well performance of WIPS scheme in tight reservoir. To facilitate methodology development, the conceptual models of tight formation and WIPS scheme were firstly described. Secondly, seepage models of tight reservoir and hydraulic fractures (HFs) were sequentially established and then dynamically coupled. Numerical simulation was utilized to validate our model. Finally, identification of flow regimes and sensitivity analysis were conducted. Our results showed that there was good agreement between our proposed model and numerical simulation; moreover, our approach also gave promising calculation speed over numerical simulation. Some expected flow regimes were significantly distorted due to WIPS. The slope of type curves which characterize the linear or bi-linear flow regime is bigger than 0.5 or 0.25. The horizontal line which characterize radial flow regime is also bigger 0.5. The smaller the oil rate, the more severely flow regimes were distorted. Well rate mainly determines the distortion of MPI curves, while fracture length, well spacing, fracture spacing mainly determine when the distortion of the MPI curves occurs. The bigger the well rate, the more severely the MPI curves are distorted. While as the well spacing decreases, fracture length increases, fracture spacing increases, occurrence of MWPI become earlier. Stress sensitivity coefficient mainly affects the MPI at the formation pseudo-radial flow stage, almost has no influence on the occurrence of MWPI. This work gains some addictive insights on multi-well performance for WIPS scheme in tight reservoir, which can provide considerable guidance on fracture properties estimation as well as well adjustment of production operation for WIPS scheme.

As a promising technology to improve shale gas (SG) recovery and CO2 storage capacity, the multi-well pads (MWPs) scheme has gained more and more attention. The semi-analytical pressure-buildup method has been used to estimate CO2 storage capacity. It focuses on single multi-fractured horizontal wells (SMFHWs) and does not consider multi-well pressure interference (MWPI) induced by the MWPs scheme. This severely limits the application of this method as incidences of multi-well pressure interference have been widely reported. This paper proposed a new methodology to optimize the injection strategy of the MWPs scheme and maximize CO2 storage capacity. The new method implements numerical discretization, the superposition theory, Gauss elimination, and the Stehfest numerical algorithm to obtain pressure-buildup solutions for the MWPs scheme. The solution by the new method was validated with numerical simulation and pressure-buildup curves were generated to identify MWPI. Using the new method, we observed that the fracture number and fracture half-length have a positive influence on CO2 storage capacity. Both can be approximately related to the CO2 storage capacity by a linear correlation. For a given injection pressure, there is an optimal fracture number; the bigger the limited injection pressure, the smaller the optimal fracture number. Stress sensitivity has positive influences on CO2 storage capacity, thus extending the injection period would improve CO2 storage capacity. This work gains some insights into the CO2 storage capacity of the MWPs scheme in depleted SG reservoirs, and provides considerable guidance on injection strategies to maximize CO2 storage capacity in depleted SG reservoirs.