首页> 外文会议>SPE Liquids-Rich Basins Conference - North America >Modeling Terminal Decline Rate in Flow Regime Transition using AlternatingConditional Expectation Non-Linear Regression Methods
【24h】

Modeling Terminal Decline Rate in Flow Regime Transition using AlternatingConditional Expectation Non-Linear Regression Methods

机译:使用交替期望非线性回归方法模拟终端衰减率

获取原文
获取外文期刊封面目录资料

摘要

Accurate EUR estimation is a critical component of the oil and gas asset evaluation process and has becomeincreasingly important in de-risking investments in shale plays. Hybridized decline curve analysis hasemerged as an industry-wide best practice for this process. This method of interpretation is dependent on theaccuracy of the estimated terminal decline rate or switch point. Accurately predicting the terminal declinerate for wells with insufficient production history, has proven difficult. This issue is further aggravatedin emerging basins and regions of development, as well as complications associated with parent-childrelationships in developed acreages. The present paper tackles these challenges by using a statisticalapproach to predict the switch point and onset of terminal decline rates in unconventional shale plays. Typical production profiles in unconventional shales are marked by high initial declines and long transientflow regimes, followed by a transition to boundary dominated flow as the pressure transient reaches theboundaries of the effected reservoir. The decline rate at this switch point, as well as the duration to getto it can vary significantly and is dependent on a wide range of variables. The present paper tacklesthis multivariable problem by using an ACE (alternating conditional expectation) non-linear regressionmodel to predict the switch point. Variables used to predict this change in flow regime include: GammaRay, Resistivity (Deep), RHOB, NPHI, formation thickness, WOR, GOR, completion design, proppantamount per foot, perforated interval, and production performance amongst others. In order to account forthe impact on production, behavior from infill development and parent-child relationship discrepancies,date- dependent 3D well spacing was calculated and incorporated as a variable in the statistical model. Thisprocess was tested and applied to a large dataset of wells in the middle Bakken formation in the WillistonBasin.
机译:准确的EUR估计是石油和天然气资产评估过程的关键组成部分,并在失败风险的页岩剧投资中变得变得非常重要。杂交的下降曲线分析作为这种过程的行业最佳实践。这种解释方法取决于估计的终端衰落率或切换点的TheAcuracy。准确地预测井中的井中的井中的生产历史不足,已经证明困难。这个问题是进一步的加剧毒素新出现的盆地和发展区域,以及与发达的种植面积的亲子女征相关的并发症。本文通过使用统计资料来预测非传统页岩竞争中的终端衰退率的开关点和发作来解决这些挑战。在非传统节宝中的典型生产曲线标志着高初始下降和长期瞬间流动制度,其次是由于压力瞬态到达所做的储层的ouderies而过渡到边界主导流量。此切换点的下降率,以及持续时间才能显着变化,并取决于各种变量。本文通过使用ACE(交替的条件期望)非线性回归模型来预测切换点来实现多变量问题。用于预测流动制度变化的变量包括:伽马河,电阻率(深),Rhob,NPHI,形成厚度,Wor,GOR,完成设计,每英尺,穿孔间隔和其他人的生产性能。为了通过对生产的影响,从填充开发和亲子关系差异的行为,计算并在统计模型中作为变量并入到变量中。在Willistonbasin中测试了该处理并应用于中间Bakken的井中的大型数据集。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号