GLGuanxing Luo

Guanxing Luo

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

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Previous Organizations / Institutes

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Guanxing Luo has a total of 20 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Evaluation Method for Deep and Ultra-Deep Shale Oil Resource Conversion

    by Xinping Yang, Dongsheng Yao, Jianwei Wang, Guanxing Luo, Teng Zhao, Hong Pan, Chuanchuan Qian, Lifeng Zhang, Li Wang, Wenying Wu, et al.

    In response to the problems of deteriorating quality of newly added reserves of deep and ultra-deep shale oil, significant differences in well efficiency among similar sweet spots, and difficulty in converting resources and production capacity, a deep and ultra-deep shale oil resource conversion evaluation method is proposed based on the entire process of shale oil development. Based on the production dynamics during the initial stage of production, we establish oil well classification standards for deep and ultra-deep shale oil and obtain two types of shale oil development unit classification standards. We construct well efficiency response indicators for development units, well efficiency index and well efficiency index, quantitatively characterizing the comprehensive well efficiency response within the development unit. We construct a production capacity evaluation system for the development of sweet spots that integrates resource utilization, technological economy, and business management. We use the fuzzy comprehensive evaluation method to obtain sweet spot evaluation scores and grades and quantitatively characterize the differences in production capacity construction for the development of sweet spots. On this basis, the “Resource–Productivity Matching Five Step Method” is proposed, which couples the sweet spot evaluation results with the well efficiency index to obtain the final score and evaluation results of resource conversion. The instance application of the M development unit shows that its overall resource conversion efficiency is not high, with only one type of area being a good match and the other areas being basic matches. The evaluation results are relative. This method achieves the integration of “sweet spot advantage (comprehensive score)—well efficiency response (well efficiency index)—conversion effect (final score)” and can identify false matches, improve the objectivity and reliability of evaluation results, and provide a scientific basis and technical support for shale oil block screening, well location deployment, construction planning and other research.

  • Open Access

    Production Decline Analysis of Tight Conglomerate Reservoirs with Small Well Spacing, Based on the Fractal Characteristics of Fracture Networks

    by Xiaoshan Li, Junqiang Song, Hong Pan, Kaifang Gu, Shuo Wang, Liu Yang, Haoyu You, Li Wang, Xin Wang, Shihong Li, et al.

    The conglomerate matrix and fracture propagation are special in tight conglomerate reservoir with small well spacing. In this article, the fractal propagation characteristics of the fracture network in conglomerate reservoirs are described by experiment and a micro-mathematical model. According to the core slice, the conglomerate reservoir matrix presents the multi-modal pore structure, described as the “pseudo-dual-media” model. Given the above, the unsteady seepage mathematical model, comprehensively considering the fractal fracture network, stress sensitivity of main fractures, and threshold pressure gradient of the reservoir matrix, was developed and analytically solved. The Blasingame type curves for production decline analysis were plotted, and the sensitive parameters were analyzed. The field application was performed for validation. The research results show that the fractal dimension decides the complexity of the fracture network distribution. As it increases, the unsteady flow occurs earlier, and the boundary flow is delayed. The anomalous diffusion exponent represents the smoothness of crude oil migration and a higher value leads to higher resistance to oil migration and larger pressure drawdown for the same production rate. The growth of the threshold pressure gradient within a certain range can result in a localized downward shift of the type curves. The field application in a conglomerate oil reservoir showed that the presented model presents a fitting accuracy 10% higher than that of the conventional SRV model and has high reliability and precision for the production performance evaluation of the small-well-spacing development of tight conglomerate reservoirs.