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基于灰色关联法的页岩气水平井产能评价及预测 被引量:10

Production Evaluation and Prediction of Horizontal Shale Gas Wells Based on Grey Correlation Method
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摘要 页岩气水平井产能差异明显、影响因素众多,地质甜点评价阶段和压裂改造阶段都可左右其产量.为此,以威远页岩区块10口典型水平井为例,综合考虑地质与工程因素,利用灰色关联法筛选产能主控因素并建立产能评价模型,从而实现产量快速预测.结果表明:页岩气水平井能否获得高产由地质因素和工程因素共同决定,两者相辅相成,筛选出7个产能主控因素分别为:优质储层压裂长度、孔隙度、压力系数、TOC、优质储层厚度、优质储层钻遇长度和压裂液用量;基于水平井测试产量与产能综合评价因子相关关系可快速预测气井产量,预测结果与实际测试产量平均相对误差为16%,预测效果较好,验证了该方法的可靠性和准确性. There are many factors that can affect the production of horizontal shale gas wells during the geological sweet spot evaluation and stimulation stage,which has great difference among different wells.Based on this,10 horizontal wells in the Weiyuan shale gas field are taken as the research objects.Taking geological and engineering factors into account,the main controlling factors of production are selected by means of the grey correlation method and the production evaluation model is established,so as to achieve rapid production prediction.Results indicate that whether horizontal shale gas wells can obtain high production is determined by both geological and engineering factors.Seven main factors controlling production are screened out,which are as follows:fracturing length of high-quality reservoir,porosity,pressure coefficient,TOC,thickness of high-quality reservoir,drilling length of high-quality reservoir and fracturing fluid volume.According to the correlation between test production and production comprehensive evaluation factor of horizontal wells,the production of gas wells can be predicted rapidly.The average relative error between the prediction result and the real test production is 16% and the prediction effect is good,which verifies the reliability and accuracy of this method.
作者 耿晓燕 何畅 万玉金 GENG Xiao-yan;HE Chang;WAN Yu-jin(PetroChina Research Institute of Petroleum Exploration&Development,Beijing 00083,China)
出处 《数学的实践与认识》 北大核心 2020年第19期100-106,共7页 Mathematics in Practice and Theory
基金 “十三五”国家重大专项“页岩气气藏工程及采气工艺技术”之课题6“页岩气开发规模预测和开发模式”(2016ZX05037-006).
关键词 页岩气 产量主控因素 产量预测 灰色关联法 量化评价 shale gas production controlling factors production prediction grey correlation method quantitative evaluation
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