多点地质统计建模在扇三角洲沉积中的应用

doi:10.11885/j.issn.1674-5086.2020.07.01.01

摘要/Abstract

摘要： K油田处于开发前期方案编制阶段，钻井资料少，地震资料品质较差，储层的空间展布预测存在较大不确定性。综合油田取芯、测井、测压及地震等资料，分析储层为扇三角洲前缘沉积，发育分流河道、溢岸和河口坝等多种沉积微相，采用传统地质建模方法难以精确表征K油田的沉积模式。通过采用多点地质统计建模方法，融入反映地质认识的训练图像，结合已钻井垂向微相组合特征及储层平面展布规律，实现多维约束建立K油田相模型。模拟结果显示，由多点地质统计建模模拟的K油田相模型较好地表征了分流河道的展布形态及沉积微相之间的空间组合关系，且地质不确定性较低，更加符合地质认识，对油田开发方案的编制具有较强的指导意义，同时对类似沉积相建模具有一定推广意义。

关键词: 多点地质统计, 东非裂谷, 沉积模式, 训练图像, 扇三角洲

Abstract: K Oilfield is in the stage of pre-development plan preparation. Due to inadequate drilling data and poor quality of seismic data, there are large uncertainties in the prediction of the spatial distribution of reservoirs. Through analysis of the core, logging, pressure, seismic data, we find out that the reservoir is a fan delta front sediment, with various sedimentary microfacies such as distributary channel, overbank and mouth bar. It is difficult to accurately depict the sedimentary facies model of the K Oilfield using traditional geological modeling methods. By using multi-point geostatistical modeling methods, incorporating training images reflecting geological knowledge, combined with the characteristics of the vertical microfacies combination of drilling and the distribution regularity of reservoirs, the K Oilfield face model is established with multi-dimensional constraints. The simulation results show that the K Oilfield facies model simulated by multi-point geological statistics modeling better represents the distributary channel distribution morphology and the spatial association relationship between sedimentary microfacies, and the geological uncertainty is low, which is more in line with the geological understanding. The research results have a strong guiding significance for the preparation of oilfield development plan, and also has a certain extension significance for similar sedimentary facies modeling.

Key words: multi-point geostatistical, East African Rift, sedimentary model, training image, fan delta

中图分类号:

TE122

刘钧, 杨希濮, 吕文睿, 徐伟, 刘广为. 多点地质统计建模在扇三角洲沉积中的应用[J]. 西南石油大学学报(自然科学版), 2022, 44(5): 47-60.

LIU Jun, YANG Xipu, Lü Wenrui, XU Wei, LIU Guangwei. Application of Multi-point Geostatistical Modeling in Fan Delta Sedimentary Model[J]. Journal of Southwest Petroleum University(Science & Technology Edition), 2022, 44(5): 47-60.

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http://journal15.magtechjournal.com/Jwk_xnzk/CN/Y2022/V44/I5/47

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