Avocet production operations software solution
Field-level decision support system enabling you to hit all of your production targets
Field-level decision support system enabling you to hit all of your production targets.
Implementing smart production operations to improve operational performance and efficiency
This project took place on a remote well pad, in a brownfield in the Amazonian region of Ecuador. Smart production operations (SPO) have been implemented as a comprehensive automated solution in the field, to improve operational performance and efficiency.
This project deployed digital solutions as a game changer for operational efficiency and production optimization in a challenging location. This well pad was chosen due to its remote location ( a three hour round trip from base), a low mean time between failures (MTBF) for ESPs, high production losses from flow assurance events, lack of early identification and response for debottlenecking. It was further hindered by a lack of well tests and its reliance on manual operations.
Access was also frequently interrupted by local strikes, delaying responses to corrective actions. At the outset of the project six key performance objectives were identified, to increase oil production, reduce production losses, increase crew and people efficiency, reduce the well failure index, reduce CO2 emissions, and increase chemical treatment efficiency and reliability.
The SPO project implemented in this field has shown remarkable results against all six of the benchmarking performance objectives. The solutions implemented have resulted in improved production, with a 1.5% average increase and production losses reduced by 48%. People efficiency also increased by 60%, due to the reduction in time taken to perform activities remotely from the monitoring center compared with when they were previously performed manually on location.
After eight months of implementation, current trends show the well failure index will be reduced by as much as 25% and three rigless interventions have been avoided saving upwards of USD 30 thousand.
The chemical treatment system has shown even greater improvement with a 99% increase in reliability.
The project also achieved a significant improvement in carbon footprint with a 57% reduction in CO2 emissions, which translates to a reduction of 1.5 tons of CO2 emissions per month.
This was due to a reduction in the number of field visits, made possible by digitally enabled remote and autonomous operations.