摘要
深层缝洞型碳酸盐岩油藏是多期地质构造和岩溶作用改造形成的油藏,缝洞体结构复杂、非均质性强,常规的碎屑岩油藏井间连通预测技术不适用。基于静、动态数据结合多重分形、曲线相似度分析等技术,自动提取缝洞单元不同机理下相邻井响应程度等生产动态特征参数,实现井间连通程度自动评价。利用深度残差网络实现地震多属性融合刻画储集体空间结构,采用强化学习和多目标算法自动搜索三维连通路径。以塔里木盆地塔河油田不同岩溶背景典型缝洞单元为例,自动提取的动态响应特征及三维连通路径的展布形态说明裂缝网络是风化壳岩溶井间主要连通通道,多向连通性好;主断裂和次级断裂是断控岩溶井间的主要通道,沿断裂呈条带状连通;古暗河岩溶沿多层暗河连通,局部充填垮塌具有分段性。研究成果对深层缝洞型油藏剩余油与提高采收率研究具有较大的指导意义。
Deep fractured-vuggy carbonate reservoirs,usually a result of multi-stage tectonic movements and paleo-karst modification,are complex in structure and strong in heterogeneity.Conventional connectivity identification methods,primarily based on clastic rock reservoirs,are not suitable for carbonate reservoirs.This research aims to realize an automatic evaluation of inter-well connectivity by studying static and dynamic data and incorporating techniques such as multifractal and curve similarity analyses into the evaluation.These techniques can be employed to extract characteristic dynamic parameters and detect response level of neighboring wells under different mechanisms.Deep residual networks are used to integrate multi-attribute seismic data for characterizing the spatial structure of reservoirs.Additionally,reinforcement learning and multi-objective algorithms are also employed to automatically search for three-dimensional connectivity paths.Extracted dynamic response features and the distribution patterns of three-dimensional connectivity paths in typical fracture-cavity units in the Tahe oilfield with different karst backgrounds demonstrate that the fracture network serves as the primary communication channel among wells in weathered crust karst,exhibiting good multidirectional connectivity.The main and secondary faults are the primary channels connecting between wells within faultcontrolled karst oil reservoirs,forming a strip-like connectivity pattern along the faults.The connectivity of paleounderground river karst along multiple layers of underground river networks with local filling and collapse exhibiting segmental characteristics.The research results are of guiding significance for exploring remaining oil and enhancing recovery of deep fractured-vuggy reservoirs.
作者
康志江
张冬梅
张振坤
王睿奇
姜文斌
刘坤岩
KANG Zhijiang;ZHANG Dongmei;ZHANG Zhenkun;WANG Ruiqi;JIANG Wenbing;LIU Kunyan(Petroleum Exploration and Production Research Institute,SINOPEC,Beijing 102206,China;School of Computer Science,China University of Geosciences,Wuhan,Hubei 430074,China)
出处
《石油与天然气地质》
EI
CAS
CSCD
北大核心
2023年第5期1290-1299,共10页
Oil & Gas Geology
基金
国家自然科学基金联合基金重点项目(U19B6003)。
关键词
强化学习
多目标优化
三维连通路径
地震多属性融合
岩溶系统
缝洞型油藏
塔河油田
塔里木盆地
reinforcement learning
multi-objective algorithm
three-dimensional connectivity path
fusion of seismic multi-attribute
karst system
fractured-vuggy reservoir
Tahe oilfield
