Determination of reservoirs' relative efficiency and a way to optimize inefficient ones : application of data envelopment analysis and reservoir simulation model

Abstract

The current practice measuring oil reservoir efficiency uses ratio analysis from cumulative oil production to oil initially in place. It does not mention any input parameters that contribute to the output. There is no explanation which input is in excess to generate output, and which oil reservoirs are measured on an individual basis, leaving no indication of efficient input targets from inefficient ones. This research measures relative efficiencies of oil reservoirs and identifies the inefficient ones. The efficiency is measured as a distance between the input and output quantity of a decision making unit (DMU) and the input and output quantity defined as a frontier line. A slack improvement is used to modify the input to optimise an inefficient DMU. Started with performing optimisation of each DMU for no further action (NFA) stage and enhanced oil recovery (EOR) process by utilizing a reservoir simulation model (RSM), then efficiency of each DMU is measured using DEA method. Utilising this method, the efficient input target from inefficient ones is estimated to measure a slack improvement to modify the RSM inefficient inputs before rerunning the model. To this end, 12 oil reservoirs as DMUs operating in NFA and EOR development stages are analysed. The constant return to scale (CRS) input-oriented model is selected to measure the efficiency. The first case shows that DMU8 has 100% efficiency and DMU11 is found to be the least one and therefore it is selected for optimisation. The efficient input target generated by the DEA model is to recalculate the output using RSM. By rearranging the well locations, RSM can produce the same output as the initial input. The number of producers could be reduced from 21 to 5 wells to get the same level of output. Similar for the EOR case, we reduce the number of producers from 21 to 12 wells and injectors from 6 to 4 wells to get the same level of output. The contributions of the research include methodological and practical contributions. The methodological contribution includes developing an integrated DEA model and RSM to improve an inefficient DMU to become an efficient one and developing a framework optimization model to maximize oil recovery. The practical contribution includes assigning an oil reservoir as a DMU in the DEA model for measuring its efficiency with multiple inputs and outputs. The other practical contribution is providing a solution to improve a project economic by reducing its cost to get the same output.