Tracking the Performance of Strategically Significant EOR Pilot: Zooming into Inter-Well Connectivity

Abstract

North Kuwait has planned EOR activities to boost ultimate recoveries in multiple reservoirs. The reservoir with the highest priority on the EOR activity Gantt chart is Alkaline Surfactant Polymer (ASP) flood for Sabiriyah Mauddud due to significant incremental recovery estimated based on past SWCT tests. Prior to the initiation of ASP injection, slated pilot area is under intensive plumbing for insights into the inter-well connectivity. The paper proposal aims to share the actions taken up, analysis done and tracking of dynamic data for the area located within & adjacent to the EOR pilot area. Data acquisition for the pilot area wells (4 injectors; 2 observation wells & 1 producer) has been done in two phases — (a) during the drilling of the wells, cores/ RFT pressures/ Log suites/ PVT samples have been taken and (b) during the injection of sea water into the EOR pilot injectors, time lapse pressure-production data/ surveillance information & tracer sampling/ analysis have been done to understand the inter-well connectivity; flag the uncertainties and de-risk the EOR pilot as a preparatory background for studies & ASP injection. Connectivity between wells within the pilot & surrounding area under active water flood has been established. Pathways for quick fluid/ flux movements have been identified and calibrated with the petrophysical data. Tight zones or compartments within the pilot area have been examined. Uncertainty regarding thief zones within & outside the pilot area has been evaluated. A comprehensive data integration indicates that continuing with ASP injection will be optimal, with minimal losses/ escape to the area outside the 5-spot EOR pattern. De-risking the upcoming ASP injection via proper data acquisition, interpretation & integration during the preliminary water flood flushing stage is one of the best industry practice.

An integrated Shannon Entropy and reference ideal method for the selection of enhanced oil recovery pilot areas based on an unsupervised machine learning algorithm

“…where t 1 is the start time of production, T is the overall time of econometry, P o is the unit price of oil, q o is the oil production rate, C prod w is the unit cost of handling the produced water, C prod q is the water production rate, C inj w is the unit cost of injecting water, q inj w is the water injection rate, C o is the unit operating cost per barrel of produced oil and r is the discount rate. R(t 0 ) is the initial capital expenditure, as shown in equation (2), where C facility is the cost of facility installation, n well is the entire number of injection and production wells and C well is the drilling cost of a well. Consequently, the optimal pilot size has the highest NPV.…”

“…Pilot design plays a vital role in the road map of EOR planning and risk reduction. Therefore, EOR pilots are conducted to reduce uncertainty in EOR performance [1][2][3][4]. In the last 50 years, a significant number of EOR field pilots has been studied and the gained experience has been used in the oil and gas industry [5].…”