Petro-Elastic Models: How Many and at What Scale?

Abstract

This paper describes an integrated workflow that determines the minimum number of petro elastic models required to adequately predict elastic properties for a given flow scale. The workflow involves the formulation of scale-dependent petro-elastic models (PEM) and petroelastic facies from well logs. Then through an error evaluation technique, determines the minimum number of PEMs required and the maximum vertical grid size limit for the flow scale. The validity of the fine scale PEMs across different scales is also tested in the workflow.Elastic properties of reservoir rocks can be predicted through petro-elastic models which relate fluid and intrinsic reservoir properties to elastic properties through mathematical functions or rock physics models. Although we would like to generate PEMs at flow scale, very often the PEMs are generated from logs that are consistent with core data. A PEM is lithology and rock fabric specific. In an upscaled flow model, the lithologies or textures are mixed. Fine scale PEMs may no longer adequately describe the elastic properties of the reservoir at flow and seismic scale.Prediction is improved in a flow model that integrates all available measurements. Scale inconsistencies of the measurements need to be addressed for better integration and prediction. In this paper we will show that through a unique and iterative approach, PEMs must be generated at flow scale for improved integration. The methodology has been tested with synthetic data and resulted in a better predictive flow scale model, which is consistent across all scale resolutions.

Bayesian stochastic inversion with petro-elastic relation to quantify thin gas sands of Khadro Formation, Zamzama gas field

“…PEMs characterize the reservoirs' identified litho-facies by modeling the precise elastic responses from their petrophysical properties (Alfred et al, 2008;Mavko et al, 2020). The major outcomes of PEMs included Vp, Vs, ρ and their combinations, compensating for poor hole conditions, insensitivity of the recording tool, missing elastic logs especially s-wave, and ultimately featuring a good separation of the pay and nonpay facies in the elastic domain (Yusoff et al, 2014;Zeb and Murrell, 2015;Carrasquero et al, 2020).…”

Finding a Petro-elastic Model Suitable for Sim2seis Calculation

“…In an integrated sim2seis study, three different vertical scales are dealt with: log scale, simulation model scale, and the seismic scale. Differing concepts and approaches associated with the PEM scale are addressed in the literature (for example, Menezes et al, 2006 andAlfred et al, 2008). In this study we evaluate the effect of upscaling the log data to the seismic scale.…”

“…An upscaling that maintains geological consistency is a good first choice approach, however the seismic responses are invariably different at each scale (Figure 3). Alfred et al, (2008) attributed the resultant upscaling error to a mixing of lithologies. However, we find that even in a geologically consistent upscaling in which mixing between sand and shale intervals is avoided, errors arise due predominantly to distortions of the phase spectrum of the reflectivity series.…”