油气藏评价与开发 ›› 2024, Vol. 14 ›› Issue (4): 577-585.doi: 10.13809/j.cnki.cn32-1825/te.2024.04.007

• 方法理论 • 上一篇    下一篇

直觉模糊MABAC法在低渗碳酸盐岩气藏有利区优选中的应用

闵超1,2,3(),李映君1,2,李小刚3,华青4,张娜4   

  1. 1.西南石油大学理学院,四川 成都 610500
    2.西南石油大学人工智能研究院,四川 成都 610500
    3.西南石油大学油气藏地质及开发工程全国重点实验室,四川 成都 610500
    4.中国石油西南油气田公司重庆气矿,重庆 400700
  • 收稿日期:2023-09-05 出版日期:2024-08-26 发布日期:2024-09-10
  • 作者简介:闵超(1982—),男,博士,教授,从事最优化方法与不确定性理论在油气田开发中的应用研究工作。地址:四川省成都市新都区新都大道8号,邮政编码:610500。E-mail: minchao@swpu.edu.cn
  • 基金资助:
    成都市国际合作项目“基于深度学习的孔隙网络渗流模拟理论和技术探讨”(2020-GH02-00023-HZ)

Application of intuitive fuzzy MABAC method in optimizing favorable areas of low permeability carbonate gas reservoirs

MIN Chao1,2,3(),LI Yingjun1,2,LI Xiaogang3,HUA Qing4,ZHANG Na4   

  1. 1. School of Science, Southwest Petroleum University, Chengdu, Sichuan 610500, China
    2. Institute for Artificial Intelligence, Southwest Petroleum University, Chengdu, Sichuan 610500, China
    3. State Key Laboratory of Oil and Gas Reservoir Geology and Development Engineering, Southwest Petroleum University, Chengdu, Sichuan 610500, China
    4. PetroChina Southwest Oil and Gas Field Company, Chongqing 400700, China
  • Received:2023-09-05 Online:2024-08-26 Published:2024-09-10

摘要:

低渗碳酸盐岩气藏地质构造和储层特征复杂,数据获取和解释的不确定性较高,导致有利区优选的难度较大。提出了最优最劣法(BWM)赋权下的直觉模糊MABAC(多属性边界近似区域比较)法低渗碳酸盐岩有利区优选模型。首先,根据低渗碳酸盐岩地质特征、生烃能力和储气能力等信息,建立综合考虑低渗碳酸盐岩成藏的地质条件、施工条件的综合评价指标体系;然后利用BWM方法确定各关键评价指标权重,同时考虑多个因素对不同的油气田的影响并掌握因素之间的优先级关系;最后,利用直觉模糊信息替代精确信息,建立改进的直觉模糊多属性决策模型,对低渗碳酸盐岩气藏开发有利区进行优选。利用10个碳酸盐岩气藏区块进行实验,结果表明:剩余动态储量、有效储层厚度等因素表现良好的C区块为最优。对碳酸盐岩气藏开发有利区块按照整体距离的值进行降序排序,结果为:C区>I区>H区>A区>D区>G区>J区>E区>F区>B区。将提出的直觉模糊MABAC法与现有方法进行对比,并结合数值模拟结果分析,验证了该方法的有效性和合理性。

关键词: 低渗碳酸盐岩, 有利区优选, 评价指标体系, 最优最劣法(BWM), 直觉模糊MABAC法

Abstract:

The geological structure and reservoir characteristics of low-permeability carbonate gas reservoirs are complex, and the high uncertainty in data acquisition and interpretation makes it challenging to identify optimal development areas. To address this, the study introduces an intuitionistic fuzzy Multi-Attributive Border Approximation area Comparison(MABAC) model, combined with the Best Worst Method(BWM) for weighting, to select the most suitable areas for developing these reservoirs. The approach begins by establishing a comprehensive evaluation index system that considers geological characteristics, hydrocarbon generation capacity, and gas storage capability of the low-permeability carbonate formations. This system not only integrates geological data but also considers the construction conditions relevant to these reservoirs. Using the BWM, weights for each key evaluation indicator are determined, taking into account the multifactorial impacts on various oil and gas fields and establishing the hierarchical relationships between these factors. An improved intuitionistic fuzzy multi-attribute decision-making model is then developed. This model uses intuitionistic fuzzy data instead of precise information, enhancing the selection process for favorable areas. The application of this model on ten candidate blocks indicated that Block C is the most favorable, outperforming others in terms of remaining dynamic reserves, effective reservoir thickness, and other crucial indicators. The blocks were ranked as follows based on the overall distance value: Block C > Block I > Block H > Block A > Block D > Block G > Block J > Block E > Block F > Block B. The effectiveness and rationality of the proposed intuitionistic fuzzy MABAC method were validated through comparisons with existing methods and analysis of numerical simulation results, confirming its utility in optimizing the development of low-permeability carbonate gas reservoirs.

Key words: low permeability carbonate rock, selection of favorable areas, evaluation index system, Best Worst Method(BWM), intuitive fuzzy MABAC method

中图分类号: 

  • TE155