Reservoir Fluids Saturation Diagnostic and Hydrocarbon Targets Identification Workflow

Abstract

Though there are various methods to assess reservoir performance, historical methods seem to focus the assessment on a single or couple of parameters. These include traditional methods to evaluate the reservoir sweep through average oil saturation-thickness maps, remaining oil volume maps, etc. Optimum reservoir management is a challenging and time consuming process since it usually involves analyzing many reservoir properties such as porosity, permeability, thickness, hydrocarbon saturation, fluid properties, relative permeability, net-to-gross ratio and pressures. In this work, we incorporate all these parameters into an automated workflow for reservoir diagnostics; and identification and ranking of optimum hydrocarbon (HC) targets. The proposed workflow extracts static and dynamic information from reservoir simulation outputs and performs additional post-processing calculations on each grid cell for all time steps. The methodology involves classification of the reservoir simulation grid cells based on fluid saturation, relative permeability, pressure changes and displacing phase fluxes. After that, Produced, Mobile and Immobile oil volumes are calculated for each cell. These volumes are then grouped into six categories, namely, Produced, Highly Contacted, Moderately Contacted, Minimally Contacted, Uncontacted and Immobile Oil. In addition, the workflow incorporates different indicators for determining grid cell quality. These indicators are Reservoir Opportunity Index (ROI) and Simulation Opportunity Index (SOI); and we proposed a new reservoir quality indicator that incorporate changes in pressure over time. Finally, the workflow identifies connected cells with high quality indices and ranks these regions based on size and/or grid cell quality as potential targets for infill drilling. The presented automated workflow is introduced as an integral part of well placement optimization workflow. It has been tested on several simulation models and successfully identified and ranked un-swept reservoir regions which proved through dynamic simulations to be credible future drilling targets.