An onshore oil and gas company in Eastern Europe produced from 220 oil and gas brownfields containing around 20,000 wells. Of these wells, 10,000 wells were shut-in and waiting for potential abandonment or reactivation. From the remaining producers, each well was evaluated for workover potential three to four times per year through a series of manual well by well reviews.
Seeking a method for automating the workover candidate selection process, the operator chose the PetroVisor platform for screening 500 shut-in wells to determine reactivation opportunities. A machine learning application within the platform was used to deliver a ranked list of candidates to improve oil and gas CAPEX efficiency and reduce risk. The platform integrated over 40 databases (including geologic, petroleum engineering and reservoir engineering) providing the operator with a digitized system of all well data for future use and cataloging.
The project delivered a 70% reduction in time spent screening data, an 85% decrease in overall project time and a 77% increase in CAPEX efficiency.
