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伊拉克H油田上白垩统Hartha组孔隙型碳酸盐岩储层成岩相特征及地质建模

作    者:吕 洲1,杜 潇1,王友净1,张 杰2,李 楠1,王 鼐1,王 君1,洪 亮3,郝晋进3
单    位:1 中国石油勘探开发研究院;2 中国石油杭州地质研究院;3 中国石油勘探开发研究院西北分院
基金项目:本文受中国石油天然气股份有限公司“十四五”前瞻性基础性重大科技项目等共同资助
摘    要:
孔隙性生物碎屑灰岩是中东地区主要储层类型之一,具有非均质性强、孔隙类型差异显著且微观孔隙结构 复杂等特征。成岩作用是造成上述特征的重要原因,成岩相研究是综合分析成岩作用对储层影响的重要方法。本次研究针对伊拉克H油田上白垩统Hartha组缓坡相生物碎屑灰岩,开展了岩心成岩作用表征、成岩相划分及孔喉特征 分析、成岩相测井响应及神经网络学习、成岩相空间约束条件分析及地质建模等研究工作。结果表明,研究区Hartha 组顶部HA层发育孔隙型碳酸盐岩储层,对储层质量造成影响的成岩作用主要为海水胶结作用、藏胶结作用、准同生溶蚀作用、埋藏溶蚀作用、压实作用和白云石化作用。依据成岩作用差异和孔隙类型差异,划分出5种岩心成岩相类型,分别为原生孔隙型、溶孔型、体腔孔型、晶间孔型和微孔型。将岩心成岩相及测井曲线特征进行标定,划分出3种差异较为明显的测井成岩相,通过基于岩心标定的常规测井曲线进行神经网络学习,对非取心井进行测井成岩相识别。以单井成岩相为基础,铀/钍钾比、层序界面距离、纵波时差3种属性为空间约束,建立了研究区三维成岩相模型。本次研究为孔隙性生物碎屑灰岩成岩相表征与建模提供了方法与实例。
关键词:孔喉结构;成岩作用;成岩相;地质建模;碳酸盐岩;伊拉克

Diagenetic facies and geological modeling of porous carbonate reservoir of the Upper Cretaceous Hartha Formation in H Oilfield, Iraq

Author's Name: LÜ Zhou, DU Xiao, WANG Youjing, ZHANG Jie, LI Nan, WANG Nai, WANG Jun, HONG Liang, HAO Jinjin
Institution: 
Abstract:
Porous bioclastic limestone is one of the main reservoir types in the Middle East. It usually shows the characteristics of strong reservoir heterogeneity, large permeability difference, significant pore type difference and complex microscopic pore structure. Diagenesis is an important reason for the differences in the reservoir properties of porous bioclastic limestone. In particular, the differential distribution of dissolution and cementation causes changes in pore types and microscopic pore structure, which in turn affects reservoir permeability, resulting in obvious differences in permeability under the same porosity. The study of diagenetic facies is an important method to comprehensively analyze the influence of agenesis on the reservoir. In order to quantitatively characterize the distribution characteristics of diagenetic facies and establish the corresponding diagenetic facies geological model, this paper take the bioclastic limestone of the ramp facies of the Upper retaceous Hartha Formation in Iraq H Oilfield as the research object and carry out the characterization of core diagenesis, diagenetic facies division and analysis of pore throat characteristics, diagenetic facies logging response and neural network learning, diagenetic facies space constraint analysis and geological modeling research work. The research results show that the reservoir of Hartha Formation in the study area is developed in the top of HA, with seawater cementation, burial cementation, quasi-syngenetic dissolution, burial dissolution, compaction and dolomitization. Based on the difference in diagenesis and the difference in pore types caused by diagenesis, it can be divided into five types of diagenetic facies, namely, primary pore diagenetic facies, dissolved pore diagenetic facies, moldbody cavity diagenetic facies, ntercrystalline pore diagenetic facies, and microporous diagenetic facies. After the five diagenesis types are summarized and merged into three distinct logging diagenetic facies types, neural network learning is carried out with conventional logging curves based on lithology calibration, which can effectively identify the diagenetic facies distribution of non-coring wells. Based on the controlling effect of the three attributes of uranium / thoriumpotassium ratio, sequence interface distance, and longitudinal wave time difference on diagenetic facies and taking them as spatial constraints, a three-dimensional constrained probability field of diagenetic facies is established, single-well identification data is integrated,and a three-dimensional diagenetic facies model is established. Uncertainty analysis improves the prediction accuracy of geological models. The geological modeling of diagenetic facies in this study provides a geological basis for the classification of reservoir rock types, the characterization of permeability and the distribution prediction of dominant reservoirs. The research process is based on core-conventional logging diagenetic facies identification and neural network learning. And the estimation of the spatial distribution probability volume based on the influencing factors of diagenesis provides a method and modeling example for the geological modeling of the diagenetic facies of the porous bioclastic limestone.
Keywords: pore structure; diagenesis; diagenetic facies; geological modeling; carbonate reservoir; Iraq
投稿时间:2021-09-27  
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