Abstract

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 205435, “Flow Diagnostics in High-Rate Gas Condensate Well Using Distributed Fiber-Optic Sensing and Its Validation With Conventional Production Log,” by Fuad Aziz Atakishiyev, SPE, BP, and Alessandro Delfino and Cagri Cerrahoglu, Lytt, et al. The paper has not been peer reviewed. The authors describe a machine-learning (ML) approach for processing distributed-fiber-optic-sensing (DFOS) data that enables dynamic flow-profile monitoring using a fiber-optic electric-line cable deployed in a gas condensate well and compare the method with a conventional approach. DFOS technology has the potential to provide more-efficient and dynamic flow profiles compared with traditional methods, particularly in high-rate gas wells where production logs (PL) are recorded at reduced rates to avoid tool lifting. Technology and Field Introduction DFOS surface acquisition systems launch short pulses of light into an optical fiber, then receive its backscatter and convert it into physical measurements: temperature in the case of distributed temperature sensing (DTS) and acoustic intensity in the case of distributed acoustic sensing (DAS). These systems essentially turn a fiber-optic cable into a long array of thermometers (DTS) or multifrequency microphones (DAS). The DFOS systems record the backscatter signal continuously and measure at multiple points along the fiber. The major advantage of DFOS acquisition is the ability to record data throughout time at a very high sampling frequency. Unlike traditional PL tools, insights provided by DFOS offer a real-time view of changes in production without intervention. A successful trial was performed in a high-rate gas-producing well to test the quantitative inflow profiling algorithm on DFOS data. As part of the work, conventional PL data were acquired in high-rate gas production Well A01. An electric-line cable with built-in multimode and single-mode fiber-optic line was used to acquire conventional PL data. DAS and DTS data were acquired simultaneously for approximately 30 minutes while the well produced at a gas rate of approximately 70 MMscf/D. No sand-control completions were planned for Well A01 or for other wells in the field; therefore, in addition to the identification of a quantitative inflow profile, another main objective of the study was to identify intervals with sand production.

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