Creation and utility of a large fit-for-purpose earth model in a giant mature field: Kern River field, California

Abstract

Reservoir management studies of California’s Kern River field rely on a full-field 155-million cell three-dimensional (3D) earth model. This full-field model provides input for reserves estimation as well as the identification, targeting, and ranking of remaining opportunities. The earth model is regarded as “fit for purpose” in that characteristics of the model are aligned with specific needs for reservoir management. Normalized resistivity logs from more than 12,000 wells are used to establish lithology and reservoir architecture. Temperature, steam, gas, and oil saturation logs from over 650 boreholes provide regular periodic surveillance for identifying changes in fluids and temperature. Changes in fluid contacts and saturations are integrated with reservoir architecture three times each year. These model updates are important to the development teams for staying current on changes in their project area. The integration of these data provides the basis for linked reserves and resource estimation and the identification and development of remaining opportunities. Kern River reserves and resources are estimated from the model for over 130 internal reporting entities. For asset reservoir management purposes, reserves are updated for over 160,000 entities (based on patterns, zones, and reserves) across the 12-sq-mi (31-sq-km) field. The updated reserves supply input to reserves distribution maps and spreadsheets used for evaluating workover and new development opportunities. Some of these opportunities represent heat mining of untapped hot oil zones whereas other opportunities are cold and require the introduction of steam to mobilize the oil. Using multiple reservoir property characteristics as filter criteria for identifying remaining opportunities is an important tool used at Kern River. Reservoir volumes containing hot moveable oil below steam zones in non-producing areas can be quickly and efficiently identified and prioritized with this method. This has helped lead to the success of our current field-wide horizontal infill drilling program that identifies geobodies based on these filtering criteria.