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作 者:杨斌[1] 刘晓东[1] 徐国盛[1] 周存俭[1]
机构地区:[1]"油气藏地质及开发工程"国家重点实验室成都理工大学,四川成都610059
出 处:《物探化探计算技术》2010年第1期35-40,118,共6页Computing Techniques For Geophysical and Geochemical Exploration
基 金:中国石油西南油气田分公司2005年科研计划(20050305-01-03)
摘 要:石炭系碳酸盐岩气藏是川东地区沙罐坪气田的主力气藏,属于低孔隙度、低渗透率的裂缝~孔隙型气藏。在气藏精细描述研究工作中,由于储层非均质性强,给使用常规方法进行储层评价带来了较大困难。这里使用神经网络建立岩芯刻度的储层物性参数预测模型,预测储层的孔隙度和渗透率参数与岩芯物性分析值基本吻合。根据现场提供的储层分类标准,并结合本地区研究成果,通过建立各类储层电性测井响应交会图版,首次归纳出各类储层的电性响应特征范围,综合运用神经网络参数解释模型、交会图版和电性响应特征标准表,对工区内各井进行处理识别,评价识别结果与产能测试结果有较好的吻合性,为进一步的产能评价、气藏开发方案调整,提供了重要参考。The Huanglong formation of carboniferous is main gas reservior of the Shaguanping gas field in eastern Sichuan which belongs to low porosity and low permeability crack-hole gas pool.Because of the anisotropy of the reservoir,it takes more difficult to the reservoir evaluation by use of traditional method in gas pool description.In this paper,a forecasting model of reservoir property parameter which is calibrated by property values of core is established by using the neural network.And the forecasting result perfectly matches core analysis values.According to the standard of discrimination of reservoir types formulated by gas field and the results of our study in this area,some cross plots of responding characters of electrical log in this reservoir are established and range of responding characters of electrical log in this reservoir is generalized.It is summarized in the first time that the range of responding characters of electrical log for various reservoirs.The neural network model,cross plots templates and the standard of range of responding characters of electric log in this reservoir are applied in the well log data analysis in this area,and the results are good comparing with productivity test records which provide an important reference for the deliverability evaluation and the adjustment of gas reservoir development plan.
关 键 词:沙罐坪气田 碳酸盐岩储层 测井解释 储层类型 储层评价
分 类 号:TE122.221[石油与天然气工程—油气勘探]
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