A Digital Avatar for Field Surveillance – Integrated Sand Production and Erosion Program

Author:

Dabholkar D. S.1,Gupta G.2

Affiliation:

1. SLB, Pune, India

2. SLB, Lysaker, Norway

Abstract

Abstract Oil and gas field face several unique flow assurance challenges during production lifecycle. Among all, sand production poses one of the most severe flow assurance risks. Large sand particles tend to settle in the pipeline forming pockets of sand beds while the small particles are carried away with fluid and causes erosion in (subsea and onshore) production facilities. Sand build-up in pipelines significantly reduces operational efficiency due to higher pressure demands on the system. Operational inefficiencies and frequent field shutdowns not only translate into increased operational expenditure (OPEX) but also results in higher carbon emissions and carbon footprints in the environment. An integrated sand production and erosion program (ISPEP) was developed with the aim to provide faster and precise digital solutions to enhance field surveillance and pipeline integrity. It uses comprehensive approach to understand sand transport in the system and tracks the deposition and bed forming conditions by utilizing field measurements and multiphase software outputs data ingestion, acquisition, processing, transformation, and conceptualization. It provides real-time actionable insights at locations that are experiencing erosional issues in complex production networks, and erosion rate estimates along with total metal loss due to erosion issues. Several methods are included and compared simultaneously in this program which make it robust and accurate. Field specific operational envelopes obtained from ISPEP are deployed as part of the digital solution. The program continuously monitors field conditions against these envelopes, identifies risks and alert operations personnel upon exceeding various preset thresholds. This empowers operators to better assess the erosion risks, allowing them to take the necessary corrective actions to mitigate or prevent failure. Machine learning algorithm in the backend provides automatic calibration functionality based on field's operating scenarios, sand production rates, etc. that ensures the solution is always representative of field and continue to provide reliable information. Currently, deployed at various fields with European and Asian operators, the advisory program has proven to be an asset for field's safety and integrity and is positively impacting OPEX by reducing downtime through early intervention and increasing uptime through real-time surveillance.

Publisher

SPE

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