From Logs Scale to Reservoir Scale: Upscaling of the Petroelastic Model

Abstract

Any quantitative workflow, designed to constrain reservoir models to 3D/4D seismic data, must rely on petro-elastic modelling (or PEM), which relates fluid and rock properties to elastic ones. Various scales must be accounted for: laboratory cores and well logs, geological and seismic grids, fluid flow simulator models. The petro-elastic model is generally a fine-scale model ("pem"), defined and calibrated for each specific case against core and logs data. Aiming a 4D history matching workflow at the flow model scale, we then need to validate the use of the logs-scale calibrated "pem" at a larger scale, vertically and laterally. In this paper we proposed a methodology to define an upscaled "PEM" (new set of relationships valid at reservoir-scale), by tuning a fine-scale existing "pem", adjusting the most sensitive and relevant parameters, by an optimisation procedure. Some previous studies already addressed downscaling problems (from reservoir to geological/seismic scale), but no previous work has proposed any solution for an upscaled PEM. The main results of this study, using real field data, are the following:upscaling is necessary, depending on the degree of static and dynamic heterogeneity;the optimisation procedure is successful in calibrating a fine-scale "pem" to get a reservoir-scale "PEM";the procedure is sensitive to the Backus averaging parameters, which must be defined carefully;this workflow is performed at wells in this study, but could be extended to reservoir scale, when a fine-scale geological model is available Introduction This study was motivated by the use of 4D seismic data, in particular in History-Matching. One possible approach, consists of applying the matching loop at the elastic domain level and at the reservoir scale, making use of a petro-elastic model to convert fluid properties and static rock properties into simulated elastic properties. This was developed during the HUTS project [Ref. 1, 2, 3)]. Coupling such a rock physics module, or petro-elastic model (PEM) with fluid flow modelling, the simulated elastic parameters (impedances) can be predicted before and during production. This can then enable the changes in rock and fluid properties to be compared with the changes inferred from the seismic surveys, thus providing additional information for computer-aided history matching. Other studies [Ref. 4, 5] also propose similar quantitative work, each applying a different approach in terms of the objective function used to minimising the mismatch between ‘observed’ seismic and computed impedances (PEM), and/or domain scale. There are indeed various scales to be considered and accounted for within the above mentioned 4D history matching workflow, or any quantitative approach: laboratory cores and well logs, geological and seismic grids, fluid flow simulator models. Since the PEM is to be used for seismic modelling and history matching of reservoir models, it can be applied at any of these above-mentioned scales. Other authors [Ref. 6] propose the geological scale as the domain for the history matching, thereby simulating the PEM at the same scale as the geostatistical simulation grid, i.e. generating synthetic saturation/pressure with the fluid flow simulator, downscaling to the fine geological model scale and then computing the elastic properties.

Improved normalization of time‐lapse seismic data using normalized root mean square repeatability data to improve automatic production and seismic history matching in the Nelson field

“…Secondly, there is uncertainty in the equations used to calculate the synthetic seismic data because they were derived from lab studies and they may be unsuitable for the simulation scale or for in situ calculations (Menezes and Gosselin 2006;Kazemi and Modin 2010). We found that the choice of model did not matter.…”

“…Uncertainties may arise in the prediction however, because of averaging issues when transforming from well logs to simulation cells. Secondly, there is uncertainty in the equations used to calculate the synthetic seismic data because they were derived from lab studies and they may be unsuitable for the simulation scale or for in situ calculations (Menezes and Gosselin 2006;Kazemi and Modin 2010).…”