الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
 |  | from | 141 |  |  |
| | | from | 141 | | |
Abstract
Pressure and production History Matching (HM) is a complicated task due to the high level of complexity raised by factors such as nonlinearities and handling large number of variables; which finally make it the most time and effort consumable part of simulation modelling building studies. Manual HM involves major difficulties such as controlling a large amount of information/data and many simulation runs, comparing between the simulated and observed data and manual altering the parameters in the DATA File. While the Automatic HM showed itself very risky and may led to losing the control of the process resulting a mathematically accepted model; but an unaccepted model from physics viewpoint. The goal of the presented research is to discuss the computer Assisted History Matching (AHM) new technique which guarantees the reservoir engineer to keep all variables under control and overcome the limitations of the Manual and Automatic HM techniques. Also; the research identifies the subsurface uncertain parameters with their ranges to understand which parameter(s) influence the risk factor more. The uncertain parameters may be static (impact volumes and connectivity) or dynamic (impact production and ultimate recovery factor). Sensitivity analysis will also be implied to determine the simulation response for each individual input or for groups of interacted uncertain inputs. In this study, the Manual and Assisted History Matching techniques are compared for one oil field. It identifies the subsurface uncertain parameters, and studies their influence on the risk factor. This study also identifies the Sensitivity Analysis for the variables and check their simulation response, in addition to studying the dependencies and interactions of uncertain inputs which be useful when some inputs are individually not sensitive; but they can interact with other parameters to respond significantly. Finally, a comprehensive AHM workflow using the Evolution Strategy Algorithm is applied to the mentioned oil field to study its positive effect on saving time and effort and to achieve more accurate.