Energy 2030

Organizing Committee

Final Program

Poster Exhibition Venue 2006 Proceedings


Proceedings of the Second International Energy 2030 Conference,
November 4-5, 2008, Abu Dhabi, U.A.E.

Manual versus Software Assisted History Matching Advantages and Limitations

Shawket G. Ghedan

The Petroleum Institute, UAE

Adrian Gibson

Abu Dhabi Company for Onshore Oil Operations (ADCO), UAE

Ilhan Sener

Abu Dhabi Company for Onshore Oil Operations (ADCO), UAE

Ralf Schulze-Riegert

Scandpower Petroleum Technology, Germany

Ozgur Gunal

The Petroleum Institute, UAE

Alex Diab

Scandpower Petroleum Technology, Germany

History matching is defined as the process of reconciling geologic models to the dynamic response of the reservoir. The main purpose of history matching is building a numerical simulation model which is consistent with the entire available reservoir data, i.e. geological, petrophysical and Special Core Analysis (SCAL) data as well as production data including field and well pressure, flow rates, water cuts and gas oil ratios.

Some known giant petroleum fields in the world are carbonate reservoirs characterized by a high level of heterogeneity. This level of heterogeneity necessitates the understanding of reservoir uncertainties in all levels of the reservoir modeling process including: data acquisition, geological static modeling and dynamic simulation modeling. Manual history matching of the simulation of these kinds of reservoirs often fails to cover important reservoir uncertainties. Geological models derived from static data, such as geological, well log, core and seismic data, often fail to reproduce the reservoir production history [1].

In order to obtain an acceptable description of the reservoir by history matching, many different simulation runs in completely different regions of the search space must be performed [2]. In order to capture reservoir model uncertainties within the range of model parameter uncertainties, a variety of models should be generated. They will not be distinguishable with respect to the reproduction of history data but may deliver different predictions of future reservoir performance [3]. The manual history matching process often tunes a limited set of parameters to reach to only one acceptable non-unique history matched model. In addition to this serious limitation, manual history matching is time consuming, and faces a real challenge in terms of keeping track of the model response to parameter changes and their


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