We use cookies to ensure that we give you the best experience on our website. You can change your cookie settings at any time. Otherwise, we'll assume you're OK to continue.

Durham University

Department of Mathematical Sciences


Publication details for Ian Vernon

Ferreira, C. J., Davolio, A., Schiozer, D. J., Vernon, I. & Goldstein, M. (2015), Use of Emulator and Canonical Correlation to Incorporate 4D Seismic Data in the Reduction of Uncertainty Process, EUROPEC 2015. Madrid, Spain, Society of Petroleum Engineers.

Author(s) from Durham


In petroleum engineering, simulation models are used in reservoir performance prediction and in the decision-making process. These models are complex systems, typically characterized by a vast number of input parameters. Typically, the physical state of the reservoir is highly uncertain and, thus, the appropriate parameters of the input choices are also highly uncertain. 4D seismic data can reduce significantly the uncertainty of the reservoir because it has a high area resolution, as opposed to the observed well rates and pressure. However, two main challenges are faced to calibrate the simulation model using 4D seismic data. The process can be time consuming because most models go through a series of iterations before being considered sufficiently accurate to give an adequate representation of the physical system. The consideration of 4D seismic data as an observed parameter in the form of maps would lead to an unfeasibly large number of variables to be matched. To overcome such issues, the construction of an emulator that represents the simulation model and the use of the canonical correlation technique to incorporate 4D seismic data can be used. The present study constructed a stochastic representation of the computer model called an emulator to quantify the reduction in the parameter input space. 4D seismic data was incorporated in the procedure through the canonical correlation technique. The water saturation map derived from seismic data was converted into seven canonical functions. Such functions represent the observable characteristics to be matched in the uncertainty reduction process. A high number of evaluations was necessary to identify the range of input parameters whose outputs matched the historical data (4D seismic data). The large number of evaluations justifies the use of an emulator and the reduction of uncertainties with areal characteristics shows that 4D seismic data was successfully incorporated. The emulator methodology represents a powerful tool in the analysis of complex physical problems such as history matching. The incorporation of 4D seismic data as an observable output to be matched leads to a difficult problem to be solved. However, the canonical correlation permitted a successful incorporation of such data into the problem.