新疆石油地质

新疆石油地质 ›› 2011, Vol. 32 ›› Issue (2): 181-182.

• 应用技术 • 上一篇    下一篇

基于神经网络的储集层改造效果评价技术及应用

郭大立1, 凌立苏2a, 许江文2a, 李雪彬2a, 张天翔2b   

  1. 1.西南石油大学,成都 610500;
    2.中国石油新疆油田分公司a.勘探公司;b.采油工艺研究院,新疆克拉玛依 834000
  • 收稿日期:2010-11-03 发布日期:2020-08-11
  • 作者简介:郭大立（1967-）,男,四川威远人,教授,博士生导师,油藏工程,（Tel）028-83033401（E-mail）guodali@sina.com.
  • 基金资助:
    国家科技重大专项示范工程19（2009ZX05062）部分研究成果

Response Evaluation Technique for Neural Network-Based Reservoir Modification and Its Application

GUO Da-li1, LING Li-su2, XU Jiang-wen2, LI Xue-bin2, ZHANG Tian-xiang3   

  1. 1. Southwest Petroleum University, Chengdu, Sichuan 610500, China;
    2. Exploration Company, Xinjiang Oilfield Company, PetroChina, Karamay, Xinjiang 834000, China;
    3. Research Institute of Oil Production Technology, Xinjiang Oilfield Company, PetroChina, Karamay, Xinjiang 834000, China
  • Received:2010-11-03 Published:2020-08-11

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摘要： 人工神经网络技术可通过预先提供的一批互相对应的输入输出数据,分析掌握其潜在规律,并依据此规律利用新的输入数据推算输出结果。通过分析以往储集层压后产能分析技术的不足,优选出神经网络技术,基于其基本思想,首先建立了预测储集层压裂后产能的模型和方法,重点研究了在客观条件下如何调整压裂改造相关参数（包括裂缝长度、裂缝导流能力、裂缝高度、裂缝沟通水层的程度、压裂液对地层的污染程度等5 个参数）,根据较为准确的储集层理想产能预测结果,与现行方案及其压裂效果比较,据此形成储集层改造效果评价技术,并研制出配套的软件,在准噶尔盆地西北缘勘探区块大量应用,整体符合率83.33%,取得了较好的效果。

关键词: 准噶尔盆地, 神经网络, 储集层改造, 压后分析, 效果评价, 综合评估

Abstract: Artificial neural network is a technique that can analyze and control the inherent regularity of corresponding input and output data pre-available, and obtain the estimating output results from the new input data. On the basis of this technique, this paper presents the prediction model and method for deliverability of reservoirs following hydraulic fracturing, mainly studies the relative five parameters to fracturing modification of reservoirs in normal conditions, such as fracture length, fracture conductivity, fracture height, extent of fracture communicating with aquifer, degree of damage of fracturing fluid on formation. Also, based on the comparison of more accurate prediction result of reservoir productivity with current program and fracturing effect, the reservoir modification prospect evaluation technique and corresponding software package are developed and widely used in explorative blocks in the northwestern margin of Junggar basin. The overall coincidence rate has reached 83.33%.

Key words: Junggar basin, neural network, reservoir modification, post-fracturing analysis, response evaluation, comprehensive evaluation

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