PRODUCTION OPTIMIZATION OF SANDING HORIZONTAL WELLS USING A DISTRIBUTED ACOUSTIC SENSING (DAS) SAND MONITORING SYSTEM: A CASE STUDY FROM THE ACG FIELD IN AZERBAIJAN

Abstract

This paper discusses results from the first successful de­ ployment of a predictive modelling technology that in­ forms pressure optimization procedures to help minimize sand production and increase hydrocarbon production ef­ ficiency in sand prone oil wells. The technique takes variabilities in sand production ob­ served through time across the reservoir section, inferred from downhole sand entry logs, alongside real-time sand transportation logs that monitor sand deposition in pipe as key inputs (both of which computed using a fiber op­ tic Distributed Acoustic Sensor (DAS) based Downhole sand monitoring system). This data is then combined with other time series sensor inputs, like choke position, Down Hole Pressure (DHP) and surface flowline acous­tic measurement (sand detector) to predict drawdown pressure envelopes to improve production efficiency. This paper details observations and initial field results from the first deployment of the capability in a highly deviated sand prone oil well completed with an open hole gravel pack (OHGP) completion in the BP-operated Azeri- Chirag- Gunashli (ACG) field located in the Azer­ baijan sector of the Caspian Sea. The paper will detail observations and procedures used to increase oil produc­tion by over 25% and eliminate sanding risks using the technology. The proposed workflow is part of a compre­hensive suite of downhole sand surveillance and manage­ment tools fueled by streaming analytics capabilities run on DAS data that have played a key role in managing sand production challenges in the ACG field. The technology has been applied numerous times for base protection, drawdown optimization and targeted re­ mediation. In this instance, we discuss the use of the technology to (1) identify and inform the source of sand detected at surface e.g., formation or completion accu-mulation, (2) identify formation intervals at risk of sand­ing, and (3) design advisory operational procedures for production optimization.