Title

Seismic prediction of natural fractures in series of shale oil reservoirs

单位

(1.页岩油气富集机理与有效开发国家重点实验室,北京100083;2.国家能源页岩油研发中心,北京100083;3.中国石油化工股份有限公司页岩油气勘探开发重点实验室,北京100083;4.中国石油化工股份有限公司石油勘探开发研究院,北京100083)

Organization

(1.National Key Laboratory of Corporation of Shale Oil/Gas enrichment mechanism and effective development,Beijing 100083,China;2.National energy R & D center of shale oil,Beijing 100083,China;3.Sinopec Key Laboratory of Shale Oil/Gas Exploration and Production,Beijing 100083,China;4.Sinopec Petroleum Exploration and Production Research Institute,Beijing 100083,China)

摘要

页岩层系中多尺度天然裂缝是重要的储集空间和输导体系,具有一定的独特性,在页岩纹层结构和夹层背景下,高角度垂直缝、顺层层理缝和微裂缝同时发育,这些裂缝的预测难度大。在页岩层系天然裂缝属性特征研究的基础上,提出了地震预测天然裂缝的流程,首先基于页岩各向异性岩石物理模型,采用高精度曲率方法研究大尺度高角度垂直裂缝;再基于VTI介质各向异性反演预测顺层层理缝,推导了正交各向异性介质反射系数的简化公式,并预测小尺度裂缝;最后利用人工智能建立了多信息多尺度裂缝综合预测方法。该方法取得了一定的应用效果,为裂缝参数的定量预测奠定基础。

Abstract

For shale oil reservoirs,natural fractures are principal reserving spaces and flowing channels.In shale oil reservoirs with shale laminated structures and interlayers,vertical fractures,horizontal fractures,and micro-scale fractures are well developed,but are difficult to predict using seismic data.First,we summarize the basic properties of natural fractures in shale.Then,based on a rock physics model,we predict large-scale vertical fractures using a high-accuracy curvature method,extract horizontal fracture density using VTI anisotropy inversion,and describe both vertical and horizontal fractures with orthorhombic anisotropy inversion.Finally,we present a comprehensive prediction procedure that utilizes artificial intelligence.Application results show that the proposed methods are effective for natural fracture prediction in a series of shale oil reservoirs and can provide a data foundation to predict fracture parameters quantitatively.

关键词：

页岩层系; 天然裂缝; 曲率; 各向异性; 岩石物理; 地震预测; 人工智能;

Keywords:

series of shale oil reservoirs,; natural fracture,; curvature,anisotropy,; rock physics,seismic prediction,; artificial intelligence;

基金项目

国家自然科学基金委员会-中国石油化工股份有限公司石油化工联合基金资助项目(U1663207)、国家重点基础研究发展计划项目(973计划项目)(2014CB239104)、国家重大科技专项项目(2017ZX05049-002)共同资助。

DOI

10.3969/j.issn.1000-1441.2018.04.016

页岩层系天然裂缝地震预测技术研究