Integration of Multi-Well Ultra-Deep Resistivity Inversions to Map Oil-Water Contact at Reservoir Scale

Abstract

Abstract Ultra-deep resistivity is a necessary measurement in well placement operations, for detecting secondary reservoirs over 100ft from the wellbore and steering in the optimum target zone to maximize well productivity. The data provides deeper understanding of the subsurface geology and is usually analyzed on a well-to-well basis. A new workflow has been developed to integrate data from different wells for mapping fluid contacts to optimize future well placement to maximize productivity. Ultra-deep resistivity measurements are inverted real-time to produce models of the sub-surface geology. The resulting models, along with supporting LWD data have the following applications: geomapping of the target zone (formation dip and thickness); deep detection of oil-water contacts (OWC) to maintain standoff distances; geosteering in targets avoiding reservoir exits; geomapping resistive or conductive layers above and below trajectory if present. This data has been acquired from several wells and OWC grids created based on inversions for three neighboring wells. One of the wells has a proven OWC level confirmation. The structural surfaces created reflect the distribution of the OWC in the drilling area. Inversion results integrated with geological models reduce the uncertainties for far field fluid mapping. The OWC does not have a single sustained vertical depth, it displays vertical depth variations (water coning) across the area under investigation. The general trend follows the structural surfaces of the target formation. However, the OWC level can vary along the well path up to 10-20 ft true vertical depth over 300 ft of measured depth footage. Identifying and measuring these changes during drilling helps to optimize the completion design to maximize production. Additionally, it helps to improve and optimize the planning of future wells planned for the area. Ultra-deep resistivity inversions integrated with the geological model provide critical information for OWC characterization at the reservoir scale. This new workflow helps to increase sweep efficiency and optimize the wells productivity, by taking advantage of the information available real-time to identify the position of the OWC along a target well path.