基于井震结合的南川地区页岩气储层叠后裂缝预测技术

doi:10.13809/j.cnki.cn32-1825/te.2022.03.008

摘要/Abstract

摘要：

页岩气储层天然裂缝发育,页岩裂缝对储层改造和后期压裂效果影响很大。基于井震结合的蚂蚁追踪技术进行裂缝预测,首先通过测井解释的天然裂缝,计算出井的裂缝发育密度曲线,然后通过多种模拟方法比较,选取高斯随机方法,该算法能体现页岩储层裂缝发育的非均质性特征,建立井间天然裂缝模型,最后通过协克里金算法体现井间裂缝发育属性,输入蚂蚁体属性进行质控,从而建立南川地区天然裂缝的预测模型。从预测结果来看,南川地区裂缝发育方向为北东向,平桥背斜东翼裂缝较核部发育,易形成网状缝,与实钻井吻合度高,裂缝预测技术能够指导该区的勘探开发。

关键词: 天然裂缝, 裂缝密度, 蚂蚁追踪, 页岩气储层, 南川地区

Abstract:

Natural fractures are well developed in shale gas reservoirs, which have great influence on reservoir reconstruction and later fracturing effect. Therefore, the fracture prediction is carried out by ant tracking technology based on the combination of logging and seismic. Firstly, the curves for the fracture development density of the wells are obtained by the calculation of the natural fractures by well logging. Then, by the comparison of various simulation methods, the Gaussian random method is selected, which can reflect the heterogeneity of fracture development in shale reservoir and establish the natural fracture model between wells. Finally, the Co-Kriging interpolation method is used to reflect the properties of inter-well fracture development, and ant attributes are input for the quality control in order to establish the prediction model of natural fractures in Nanchuan area. According to the prediction results, the fractures in Nanchuan area develop along the NE direction. The fractures in the east wing of Pingqiao anticline are more developed than those in the core, and the fracture network are easy to form. The prediction results are highly consistent with the actual drilling wells. This fracture prediction technology can guide the exploration and development of this area.

Key words: natural fracture, fracture density, ant tracking, shale gas reservoir, Nanchuan area

中图分类号:

TE122

孙小琴. 基于井震结合的南川地区页岩气储层叠后裂缝预测技术[J]. 油气藏评价与开发, 2022, 12(3): 462-467.

Xiaoqin SUN. Poststack fracture prediction technology of shale gas reservoir based on combination of well and seismic in Nanchuan[J]. Petroleum Reservoir Evaluation and Development, 2022, 12(3): 462-467.

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