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基于页岩现场含气量测试结果预测产能的方法
引用本文:姜志高,曹海虹,丁安徐,高和群.基于页岩现场含气量测试结果预测产能的方法[J].石油实验地质,2019,41(5):773-778.
作者姓名:姜志高  曹海虹  丁安徐  高和群
作者单位:中国石化 华东油气分公司 勘探开发研究院, 江苏 扬州 225007
基金项目:国家科技重大专项“彭水地区常压页岩气勘探开发示范工程”(2016ZX05061)资助。
摘    要:国内外还没有较好的提前预测页岩气井产能的方法,且由于含气量测试结果与后期产量差异较大,导致页岩气含气量测试在业内争议较多。通过对解吸过程剖析,初步解答了很多含气量相当的井产量差异较大的这个业内难题,认为单一含气量数据不足以表征含气性,还应该考虑其解吸过程,如解吸速率、游离气占比等因素,将解吸过程结合起来,由此定义了一个新的指数,即含气性指数,对其计算方法进行定义:含气性指数=解吸速率×游离气占比×总气量,并对其内在含义进行了分析。通过现场含气量测试数据,对产量具有相关性的因素进行筛选,挑选出含气性指数和压力系数对日产量具有明显相关性的因素,并通过含气性指数和压力系数2个因素,建立多元回归模型,得到日产量预测公式,并对模型的可靠性进行现场验证,发现此公式预测出产能与后期实际日产量高度吻合,使得今后现场含气量测试结束后,即可对其产能进行初步预测。

关 键 词:含气量测试  产能预测  含气性指数  解吸过程  游离气含量
收稿时间:2019-01-11

A method for predicting production capacity based on a shale gas content test
JIANG Zhigao,CAO Haihong,DING Anxu,GAO Hequn.A method for predicting production capacity based on a shale gas content test[J].Petroleum Geology & Experiment,2019,41(5):773-778.
Authors:JIANG Zhigao  CAO Haihong  DING Anxu  GAO Hequn
Affiliation:Research Institute of Petroleum Exploration & Development, SINOPEC East China Branch Company, Yangzhou, Jiangsu 225007, China
Abstract:At present, there is no way to predict shale gas well production capacity at home and abroad. There are many disputes because the gas content test results are different from later production. Through the analysis of the desorption process, the question as to why the output of many shale gas wells with similar gas volume is greatly different was preliminarily answered. Gas content data is not enough to characterize gas-bearing capacity, which should be taken into consideration together with the desorption process, such as desorption rate and free gas content factors. A new coefficient was defined, namely the gas content index:gas content index=desorption rate×free gas content×total gas volume. The internal meaning of the gas content index was also analyzed. Some relevant factors of shale gas production were screened through field gas content tests. Two factors, gas content index and pressure coefficient, which have an obvious correlation with daily production, were selected. A multiple regression model was established in view of these two factors. A daily output prediction formula was obtained. Daily output=0.146 7×pressure coefficient7.2×gas content index+0.086 4. The reliability of the model was verified on site, so that the capacity of shale gas wells can be preliminarily predicted after the completion of field gas content testing. 
Keywords:gas content test  productivity prediction  gas content index  desorption process  free gas content
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