Well-scale demonstration of distributed pressure sensing using fiber-optic DAS and DTS.

ABSTRACT: In this study, we used data from optical fiber-based Distributed Acoustic Sensor (DAS) and Distributed Temperature Sensor (DTS) to estimate pressure along the fiber. A machine learning workflow was developed and demonstrated using experimental datasets from gas-water flow tests conducted in a 5163-ft deep well instrumented with DAS, DTS, and four downhole pressure gauges. The workflow is successfully demonstrated on two experimental datasets, corresponding to different gas injection volumes, backpressure, injection methods, and water circulation rates. The workflow utilizes the random forest algorithm and involves a two-step process for distributed pressure prediction. In the first step, single-depth predictive modeling is performed to explore the underlying relationship between the DAS (i

SUBMITTER: Ekechukwu GK 

PROVIDER: S-EPMC8203739 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature