Application of Dynamic Allocation Factors for Waterflood and EOR Performance Management

Abstract

Field-wide displacement and EOR floods become increasingly difficult to monitor and analyze as a system matures. Dynamic effects such as slug size, well work, pressure management, and concurrent injection can all influence performance in a way that is not captured using geometric static allocation factors. By calculating dynamic allocation factors for each time step, the dynamics of field operations can be attributed to the corresponding wells. Proper allocations can influence field operating strategies by using past performance to predict future returns in the field. Building on the concept presented in 2006 by Bharat Jhaveri, the dynamic allocation factors are calculated by an iterative process that includes all injection and production data in a time-step. Production-centered allocation factors are dependent on the surrounding volumes of injection supporting the well. Injector-centered allocation factors are dependent on the surrounding production volumes that the injector supports. Interactions are monitored and tracked using a matrix style catalog for each time step. Total injection allocation factors can then be modified for EOR application by taking into account the delayed production enhancing effects caused by solvent injection. Dynamic allocation factor analysis was completed using real field data on a system with two injectors and fourteen producers. These injectors injected both water and miscible gas on regular WAG cycles. The results of the analysis were used to evaluate waterflood and EOR performance. For the waterflood, maturity, recovery, and pressure management are the metrics required to evaluate field performance. For the EOR performance, maturity, recovery, and utilization are used to optimize oil recovery. Dynamic allocation factors were able to capture lag time in injector-producer interactions, highlight non-interactions between wells owing to geological influence, and changes in reservoir streamlines during periods of shut-in wells. Traditional well allocation factors between injectors and producers are assigned based on the geometry of that pattern. This method provides a static, unchanging view of the reservoir system, regardless of the operational dynamics. A dynamic allocation factor is derived iteratively to accurately depict reservoir interactions through time. Field management can be improved using this view of how fluids in the reservoir have historically interacted. Injection targets, infill drilling, and changes to injector conformance can all be optimized through analysis employing dynamic allocation factors.

Optimizing the Utilization of Miscible Injectant at the Greater Prudhoe Bay Fields

“…A program has just been written by McElhaney et al (McElhaney 2016) to calculate the truly dynamic allocation factors for both injection and production, and this program is planned to be adopted in future RMI and EOR oil calculations at GPB.…”