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The factors affecting the remaining oil recoverable potential in ultra-high water-cut reservoirs are extremely complex， exhibiting substantial variations in their impact. Conventional methods often rely on singular indicators such as remaining oil saturation or remaining oil abundance to assess remaining oil recoverable potential， which fails to guide tapping remaining oil in ultra-high water-cut reservoirs effectively. By considering the factors affecting the remaining oil recoverable potential in these reservoirs and comprehensively characterizing the heterogeneity of reservoirs， the scale of remaining oil reserves， watered conditions， and oil/water flow capacity， we constructed a quantitative assessment indicator system to tap the remaining oil recoverable potential in ultra-high water-cut reservoirs. In addition， according to the control degree difference of the indicators on remaining oil recoverable potential， we determined the objective weights of each evaluation indicator by combining the accelerated genetic algorithm and the projection pursuit model. We constructed the remaining oil recoverable potential index to form a new quantitative assessment method of the remaining oil recoverable potential in ultra-high water-cut reservoirs. Taking the NmIL sand body of the main production layer in the south area of Bohai Q Oilfield as an example， we quantitatively assessed the remaining oil recoverable potential in ultra-high water-cut reservoirs. The results reveal that the new method can comprehensively characterize the effects of reservoir physical properties， remaining oil reserves， and dynamic characteristics of oil/water flow on the remaining oil recoverable potential in different locations and realize the differential quantitative assessment of the distribution of remaining oil recoverable potential in NmIL sand body of the main production layer. In addition， the dominant recoverable potential area is clearly characterized， and it is taken as the potential area for the subsequent adjustment of infill wells in the NmIL sand body to accurately guide the deployment of infill horizontal wells， thereby offering a novel perspective for tapping remaining oil resources in such reservoirs.

A series of bis(thiosemicarbazide)gallium (III) complexes were synthesized and characterized by infrared spectroscopy, mass spectrometry, nuclear magnetic resonance, single‐crystal x‐ray crystallography, and density functional theory (DFT) calculation. The cytotoxicity of these gallium(III) complexes (CP 1–4) was subsequently evaluated against HCT‐116, HeLa, MDA‐MB‐231, and A549 cancer cell lines, as well as the normal cell line LO2, by MTT assays. The results indicated that CP‐1 displayed potent inhibitory effects against human colorectal cancer cells (HCT‐116) (IC50 = 0.03 ± 0.01) and human breast cancer cells (MDA‐MB‐231) (IC50 = 0.02 ± 0.01), significantly outperforming cisplatin. Moreover, CP‐2 exhibited notable selectivity towards MDA‐MB‐231 cells (IC50 = 5.01 ± 0.40) with minimal toxicity towards normal cells. Mechanistic studies revealed that treatment with CP 1–2 led to elevated intracellular reactive oxygen species (ROS) levels, resulting in cell cycle arrest at different phases. Specifically, CP‐1 induced G2/M phase arrest, inhibiting cancer cell proliferation, whereas CP‐2 hindered DNA synthesis (S phase) to impede cell proliferation. Furthermore, both CP‐1 and CP‐2 caused a reduction in mitochondrial membrane potential, activating the mitochondrial apoptotic pathway and inducing apoptosis in cancer cells. Molecular docking experiments demonstrated strong interactions between CP 1–2 and protein disulfide isomerase (PDI) at the molecular level. These findings suggest that CP‐1 and CP‐2 serve as potential anticancer agents, particularly showing promising potential in the treatment of breast cancer. [ABSTRACT FROM AUTHOR]

The Lunnan oilfield, nestled within the Tarim Basin, represents a prototypical extra-low-permeability sandstone reservoir, distinguished by high-quality crude oil characterised by a low viscosity, density, and gel content. The effective exploitation of such reservoirs hinges on the implementation of carbon dioxide (CO2) flooding techniques. This study, focusing on the sandstone reservoirs of Lunnan, delves into the mechanisms of CO2-assisted oil displacement under diverse operational parameters: injection pressures, CO2 concentration levels, and variations in crude oil properties. It integrates analyses on the high-pressure, high-temperature behaviour of CO2, the dynamics of CO2 injection and expansion, prolonged core flood characteristics, and the governing principles of minimum miscible pressure transitions. The findings reveal a nuanced interplay between variables: CO2's density and viscosity initially surge with escalating injection pressures before stabilising, whereas they experience a gradual decline with increasing temperature. Enhanced CO2 injection correlates with a heightened expansion coefficient, yet the density increment of degassed crude oil remains marginal. Notably, CO2 viscosity undergoes a substantial reduction under stratigraphic pressures. The sequential application of water alternating gas (WAG) followed by continuous CO2 flooding attains oil recovery efficiency surpassing 90%, emphasising the superiority of uninterrupted CO2 injection over processes lacking profiling. The presence of non-miscible hydrocarbon gases in segmented plug drives impedes the oil displacement efficiency, underscoring the importance of CO2 purity in the displacement medium. Furthermore, a marked trend emerges in crude oil recovery rates as the replacement pressure escalates, exhibiting an initial rapid enhancement succeeded by a gradual rise. Collectively, these insights offer a robust theoretical foundation endorsing the deployment of CO2 flooding strategies for enhancing oil recovery from sandstone reservoirs, thereby contributing valuable data to the advancement of enhanced oil recovery (EOR) technologies in challenging, low-permeability environments. [ABSTRACT FROM AUTHOR]

Infill well location optimization poses significant challenges due to its complexity and time-consuming nature. Currently, determining the scope of infill wells relies heavily on field engineers' experience, often using single indices such as the remaining oil saturation or abundance of remaining oil reserves to evaluate the potential of remaining oil. However, this approach lacks effectiveness in guiding the precise tapping of remaining oil in ultra-high water cut reservoirs. To address this, our study comprehensively considers the factors influencing the recoverable potential of remaining oil in such reservoirs. We characterize the differences in reservoir heterogeneity, scale of recoverable remaining oil reserves, water flooding conditions, and oil–water flow capacity to construct a quantitative evaluation index system for the recoverable potential of remaining oil. Recognizing the varying degrees of influence of different indices on the recoverable potential of remaining oil, we determine the objective weight of each evaluation index by combining an accelerated genetic algorithm with the projection pursuit model. This approach enables the construction of a recoverable potential index for remaining oil and forms a quantitative evaluation method for the recoverable potential of remaining oil in ultra-high water cut reservoirs. Subsequently, we establish a mathematical model for infill well location optimization, integrating and optimizing the infill well location coordinates, well length, well inclination angle, and azimuth angle. Using the main layer sand body of an oilfield in Bohai as a case study, we conducted evaluations of the remaining oil potential and infill well location optimization. Our results demonstrate that the assessment of the remaining oil potential comprehensively characterizes the influence of the reservoir's physical properties and oil–water diversion capacity on the remaining oil potential across different regional positions. This evaluation can effectively guide the determination of infill well location ranges based on the evaluation results. Furthermore, infill well location optimization can effectively enhance reservoir development outcomes. [ABSTRACT FROM AUTHOR]

The development of offshore oil fields confronts challenges associated with high water cut and low displacement efficiency. Reservoir injection-production optimization stands out as an effective means to reduce costs and enhance efficiency in offshore oilfield development. The process of optimizing injection and production in offshore oil reservoirs involves designing strategies for a large number of wells and optimization time steps, constituting a large-scale, complex, and costly optimization computation problem. In recent years, with the rapid advancements in big data and artificial intelligence technologies, sophisticated evolutionary computation methods have found widespread application in reservoir injection-production optimization problems. However, the abundance of intelligent optimization algorithms raises the question of how to choose a method suitable for the complex optimization background of offshore oilfield injection-production optimization. This paper provides a detailed overview of the application of an existing differential evolution algorithm (DE), conventional surrogate-assisted evolutionary algorithm (CSAEA), and global–local surrogate-assisted differential evolution (GLSADE) in the context of practical offshore oilfield injection-production optimization problems. A comprehensive comparison of their performance differences is presented. The study concludes that the global–local surrogate-assisted evolutionary algorithm is the most suitable method for addressing the current challenges in offshore oilfield injection-production optimization. [ABSTRACT FROM AUTHOR]