Role of Automated and Accurate Well Placement in Reducing Subsurface Complexities and Optimizing Geosteering – An Example from Complex Unconventional Reservoirs

Saikia, Kalyan (Halliburton) | Shanker, Narayan (Halliburton)


Abstract With the increasing demand for hydrocarbons, unconventional reservoirs are gaining prominence and account for a large percentage of oil and gas production. However, these unconventional reservoirs inevitably include challenges that must be carefully managed while planning an extraction strategy to yield maximum recovery. This paper demonstrates the advantages of an integrated and automated well placement workflow to improve geosteering in complex unconventional reservoirs with maximum hydrocarbon recovery. Automated well placement technique is controlled by three primary components: (1) an integrated asset model; (2) availability of uninterrupted, real-time log data; and (3) appropriately selected well planning methods. Initially, a dynamically updatable model of subsurface geology is created that combines surface topography, and an initial well trajectory is planned. As the well progresses, new log data are added to the asset model, and an interpretation is made in real time. Incorporating real-time data helps to dynamically update the model and enable a comparison of planned vs. actual deviation surveys for course corrections. This procedure guides the geosteerer to update well plans, run feasibility analyses, and predict subsurface uncertainties ahead of drilling, thus, increasing the reservoir penetration and overall well productivity. Automated well placement while drilling is a relatively new concept and requires collaboration across various disciplines. Currently, such techniques are gaining importance among operators of unconventional resources as it enhances accuracy in well positioning and provides better production while reducing costs, drilling risks, and uncertainties. In addition, when targeting very thin, geologically complex reservoir layers, it provides a holistic view of the dynamically changing asset. The use of this approach will enable oil and gas operators to make collaborative, cross-domain decisions and streamline existing unconventional workflows.

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