First Hydrocarbon Discovery in Thin Clastic Reservoir in Western UAE by Applying Innovative Data Integration Solution

Abstract

Exploration is a high risk business. Hence, available data including those from offset fields have to be analyzed and reviewed critically prior to drilling a well. This becomes especially true in a marginal thin reservoir where innovative drilling and testing strategy would play a key role in deciding commercial discovery of the prospect. Flow rate is one of the basic criteria, inter alia, on which commercial viability of a prospect depends. Conventional testing strategy performed in the vertical well did not yield commercially viable flow rate. Hence, innovative approach was adopted to achieve the desired results. After drilling, multi-disciplinary data should be integrated to finalize the testing strategy, which is critical to announce the discovery to meet the criteria set by the company. Reservoir of interest is a thin clastic reservoir, which could not meet the criteria of flow rate during testing with conventional way even though volume in place assumed to be significant due to large area. After carefully reviewing all data, the flow rates were predicted with the modeling if well will be horizonalized. In order to fully evaluate the prospect, the static and dynamic model of the first vertical well was thoroughly reviewed and re-evaluated. The vertical well was tested comingled with two reservoirs having a two feet dense layer between the two. The well flowed mostly water with traces of oil. A detailed review of the test data revealed that a higher prospectivity layer exists in the overlying thin clastic reservoir above the dense and that the two reservoirs are in isolation. Based on this finding, a modeling was performed to decipher optimal horizontal well length to achieve the flow rate. It was a challenge to geo-steer the well trajectory of horizontal section in this very thin reservoir, which was successfully achieved by an active coordination of an integrated teamwork. An innovative approach was adopted by applying Wireline Formation Tester (WFT) data to confirm dynamic isolation from underlying reservoir, which is predicted to be major water contributor. Optimal horizontal well length was established by analytical model for achieving the best flow rate. The well was drilled successfully with horizontal length of 1400 ft. in thin clastic reservoir and completed with fit-for-purpose completion followed by production testing that achieved the flow rate criteria as predicted in the model. This paper summarizes the processes of: (1) data integration, (2) establishing reservoir segmentation based on static and dynamic data, (3) modeling to predict flow rate and optimal horizontal length, (4) selection of fit-for-purpose completion and (5) addressing challenges and lessons learnt during planning and execution phases.