High-Resolution Remote Mapping of Thin Sand Lobes with Novel Multilayer Mapping-While-Drilling Tool: A Case Study from Nong Yao Field Offshore Thailand

Abstract

The recent development drilling campaign at Mubadala Petroleum's offshore Nong Yao field faced many challenges, one of which is the complexity of the reservoir which consists of mixed sand-shale sequencies with thin sand lobes of varying thicknesses. To tackle these challenges and to maximize recovery, Mubadala Petroleum planned four horizontal wells for this campaign. However, the conventional methods of geosteering have limitations. For instance, the distance-to-boundary mapping tool typically does not provide large enough depth-of-investigation for the operator to see through the interbedded shale layer to identify the multiple target sand lobes, which could pose limits on the production optimization and ultimately on the final recovery rate. Fortunately, a new technology emerged at the start of the campaign with a potential for a much larger depth of investigation and a better mapping resolution. This multilayer mapping-while-drilling tool was an extension of the previous tool with additional sensors that could read deeper into the formation. Coupled with a new advanced automatic inversion process which utilizes powerful Cloud computing, the subsurface formation resistivity profiles around the wellbore could be mapped clearly up to 25 ft away from the tool, while providing a multilayer mapping with up to 8-layer mapping capability. This new technology was evaluated and applied in two wells in this campaign to resolve the above-mentioned challenges. The result was a resounding success for the Mubadala led drilling team. In this paper, the authors explain the technology, the process of evaluating and applying it to operation, and the results from applying it. This was the first time that this technology was used in Thailand and this case study summarizes a successful outcome. The mapping results from the tool will also be used to update the reservoir model during the post-job phase and provide improvements of the overall reservoir characterization of the field.