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渤海海域中深层油气精细勘探开发理论技术专栏

莱州湾沙三中三角洲储层地震相控反演预测

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  • 1. 中海石油(中国)有限公司 天津分公司渤海石油研究院,天津 300452;
    2. 中国石油大学(北京)地球物理学院,北京 102249;
    3. 油气资源与探测国家重点实验室,中国石油大学(北京),北京 102249

网络出版日期: 2021-10-27

Prediction of Seismic Facies-controlled Inversion for Delta Reservoir in the Eocene Middle Es-3 of the Laizhou Bay

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  • 1. Bohai Oilfield Research Institute, Tianjin Branch of CNOOC Ltd., Tianjin 300452, China;
    2. College of Geophysics, China University of Petroleum (Beijing), Beijing 102249, China;
    3. State Key Laboratory of Oil and Gas Resources and Exploration (China University of Petroleum, Beijing), Beijing 102249, China

Online published: 2021-10-27

摘要

垦利10-1油田位于莱北低凸起北部斜坡带,储层评价重点的沙河街组整体为复杂断块油藏,主力含油层段沙三中Ⅰ油组以辫状河三角洲沉积为主,Ⅱ油组发育高频进积型三角洲,砂体横向变化大,储层厚度薄,采用常规手段无法准确刻画进积体内部砂体边界,预测精度不高。文章利用地震相控反演技术,将沉积相特征在地震剖面上进行转化,再由储层变量先验信息随机模拟空间储层参数体,建立完整的地质统计变差函数,并创新性的引入噪声模型自适应正则化参数,实现了反演解的稳定性和分辨率都得到了提升。垦利10-1油田的实际应用表明,反演结果与盲井资料吻合较好,能够准确清晰刻画单一进积体砂泥岩的边界,符合三角洲沉积规律,实现了精准预测中深层油气藏的目的,对于今后进一步深层油气勘探开发工作具有重大的指导意义。

本文引用格式

彭 刚, 崔雪鹏, 明 君, 黄捍东, 唐何兵, 王建兴, 李 久, 赵海峰, 王宏宁 . 莱州湾沙三中三角洲储层地震相控反演预测[J]. 高校地质学报, 2021 , 27(5) : 554 -560 . DOI: 10.16108/j.issn1006-7493.2020086

Abstract

The Kenli 10-1 oilfield is located in the northern slope of the Laibei low uplift. The Eocene Shabejie Formation of key reservoir evaluation is a complex fault-block reservoir, and its main oil-bearing interval is in the No.Ⅰand No.Ⅱoil layers of the Middle Es-3 (ie., the third Member of the Shahejie Formation), which are dominated by braided river delta deposits and highfrequency prograding delta deposits respectively. The delta is characterized by fast facies change and thin sand body reservoirs. Thus, conventional methods cannot accurately characterize the boundary of the sand body inside the prograding sand body, and the prediction accuracy is low. This study used seismic facies-controlled inversion to transform sedimentary facies characteristics on seismic profiles, and then stochastically simulated the spatial reservoir parameter based on the prior information of reservoir variables. We established a complete geostatistical variogram function and innovatively introduced adaptive regularization parameters for the noise model so that the stability and resolution of the inversion solution were improved. The application in the Kenli 10-1 oilfield shows that the inversion results are in good agreement with the staple pit, which can accurately and clearly characterize the boundary of a single prograding sand body and mudstone. This is consistent with the law of sedimentary patten of delta and achieves the purpose of accurately predicting moderately- and deep-buried oil and gas reservoirs. It is of great guiding significance for further deep oil and gas exploration and development in the future.

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