完工情况

运营商量化完井调整如何推动生产

生产改进的新前沿结合了监控技术和分析,以确定哪些变量可以提高产量。

克雷格·西波拉 (Craig Cipolla),Hess 首席工程顾问。
克雷格·西波拉 (Craig Cipolla),Hess 首席工程顾问。
资料来源:Jennifer Pallanich/JPT。

每次完井后,作业者都可以对其设计进行微调。增加阶段还是减少阶段?增加支撑剂还是减少支撑剂?

但究竟是什么推动了生产改进?运营商越来越多地寻求低成本的方法来确定这一点,通常通过分析工作流程推送现成的数据来确定哪些是有效的。无论如何,为了正确完成工作,这样做到底值多少钱?

随着长期寻求的允许操作员实时优化裂缝的技术接近现实,一个问题出现了:完美的裂缝能给底线带来多少价值。

自主智能压裂 (AIF) 功能要求自动完井设备能够响应基于低成本实时测量的决策,这些决策被输入到优化模型中,然后优化模型确定更改阶段设计参数以改进阶段的价值。Hess 首席工程顾问 Craig Cipolla 在 6 月份的非常规资源技术会议 (URTeC) 上向观众表示,Hess 想知道是否值得追求这样一个技术上雄心勃勃的目标。

为了回答这个问题,Hess 进行了建模研究,以估计完美阶段的价值,详见URTeC 4044071。该研究使用了均匀性指数 (UI),这是一种量化阶段完成效率的指标。

尽管工程师在设计完井时的目标是达到完美的 UI 1.0,但“我们很少看到均匀度指数为 1。我们看到的甚至低于这个数字,”Cipolla 说道。

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Completions

Operators Quantify How Completions Tweaks Drive Production

The new frontier of production improvement combines surveillance techniques and analysis to determine which variables boost output.

Craig Cipolla, principal engineering advisor at Hess.
Craig Cipolla, principal engineering advisor at Hess.
Source: Jennifer Pallanich/JPT.

With every completion, operators can fine-tune their designs. More stages or fewer? More proppant or less?

But what actually drives production improvements? Operators are increasingly seeking low-cost means of determining just that, often pushing readily available data through analytical workflows to determine what’s working. And just what is it worth, anyway, to get the completion right?

As long-sought technology allowing operators to optimize their fractures in real time nears reality, the question arises of how much value a perfect fracture will bring to the bottom line.

Autonomous intelligent fracturing (AIF) capabilities require automated completions equipment responding to decisions that are based on low-cost, real-time measurements fed into optimization models which then determine the value of changing a stage’s design parameters to improve it. Hess wanted to know if it was worth pursuing such a technologically ambitious goal, Craig Cipolla, principal engineering advisor at Hess, told an Unconventional Resources Technology Conference (URTeC) audience in June.

To answer that question, Hess carried out modeling studies to estimate the value of the perfect stage, detailed in URTeC 4044071. That study used the uniformity index (UI), a metric that quantifies completion effectiveness of the stages.

While engineers design completions with a goal of reaching a perfect UI of 1.0, “very rarely do we see a uniformity index of 1. We see something less than that,” Cipolla said.

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