Integrating Well and Seismic Data for Reservoir Characterization: Risks and Rewards

Abstract

Developing accurate reservoir models is a key objective of oil companies worldwide. A properly constrained reservoir model can be used to quantify hydrocarbons in place and to optimize hydrocarbon production. The evaluation of the reservoirs is typically achieved using a combination of seismic and well data. Each of these data represents imperfect measurements with a certain level of error. The manner in which these errors are handled affects the integration of the two data types and determines the quality of the final reservoir model. In this paper, I discuss one of the ways that well and seismic data can be combined to form a reservoir model. A logical workflow is proposed that consists of a systematic progression from well data analysis, to rock physics analysis, to seismic inversion and finally reservoir property estimation. The workflow cannot be followed blindly and each reservoir characterization problem must be handled in a unique manner. One of the key elements to the seismic inversion component is the development of a realistic low frequency model. A sophisticated low frequency model has a significant impact on the final reservoir model. Using a series of simple examples and case histories I demonstrate that significant benefits can be obtained from following a workflow that is tailored to deal with the uncertainties that impact on the results. I also show some of the pitfalls that have the potential to create incorrect or ambiguous results. The ultimate goal is better reservoir definition, better reservoir management and higher drilling success.