Improved hydrocarbon recovery volume estimation model using integrated asset modelling (IAM) approach

Abstract

An Integrated Asset Modelling for reservoir X is presented and the results were compared to the individual model. A sensitivity study was conducted to identify the most critical and sensitive geological, reservoir, production technology and facilities parameters towards hydrocarbon prediction. The individual model construction for REVEAL reservoir model, PROSPER well model, GAP network model and RESOLVE platform. This base case integrated model was used for hydrocarbon prediction including cumulative oil production and hydrocarbon recovery. The results of the sensitivity analysis are shown using a tornado chart and spider plot. Complete governing equations and the method is described in detail to permit readers to replicate all results. For the sensitivity analysis, ten parameters were selected from geological, reservoir, wells and facilities input parameters. It can be concluded that the Integrated Asset Modelling giving the similar results with the individual model and the topmost sensitive parameters are Initial Oil Column and Net To Gross (NTG) which are 70% and 30% increment respectively. The novelty of the integrated asset modelling approach is in the ability to combine reservoir, well and network models to predict the critical parameters affecting hydrocarbon volumetric prediction.