An Integrated Work Flow for a Comprehensive Evaluation of Thin, Silty Hydrocarbon-Reservoir Sequences

Abstract

Summary A robust work flow is established to identify low-resistivity pay (LRP) in thinly laminated sands with silty and/or shaly layers. The work flow integrates data from gas-while-drilling, conventional logging, and nuclear-magnetic-resonance (NMR) logging for picking intervals for further examination with a wireline formation tester (WFT). A mini-drill-stem test (DST) is performed by means of a WFT equipped with either a single probe (SP) or a dual packer (DP) to determine the fluid type and productivity of each individual level. Two field examples are presented to compare well performance predicted by the microscale mini-DSTs with macroscale production tests. In both cases, the traditional DST is eliminated from the drilling/completion program. The final verification consists of comparing contributions of individual levels derived from the mini-DSTs with production logs. In the first case, mini-DSTs are able to provide the fluid type and individual-level transmissibility (kh/μ) for eight out of 13 distinct levels. A cost-effective approach of running mini-DSTs by means of a WFT equipped with a single probe is demonstrated to investigate multiple levels in the thin-hydrocarbon reservoir sequence. Guidelines are provided as to when a WFT with a DP is to be deployed to perform a mini-DST in a laminated formation. In the second case, the same work flow was applied to derive the fluid type and transmissibility for two wells consisting of more than 30 distinct levels in the same field. After integrating mini-DST results from the two wells 750 m apart, a framework is constructed to establish both vertical and lateral heterogeneities of thinly laminated reservoirs. The integration helps visualize the multiple-layer reservoir. Our examples confirm that mini-DSTs effectively define individual-layer producibilities in multiple-layered reservoirs. The benefits are illustrated through case histories that demonstrate our ability to manage expectations of well performance in thin hydrocarbon-reservoir sequences.