Assessment and Reduction of Uncertainty in Fault Seal Analysis for Hydrocarbon Fluid Flow Prediction

Jones, Philip A.¹, Stephen R. Freeman², Simon D. Harris², Rob J. Knipe², Raoul R.D. Treverton², P. William Bradbury² (1) Rock Deformation Research Limited, Leeds, United Kingdom (2) Rock Deformation Research Limited,

A new technique for assessing and capturing uncertainty in fault seal analysis of hydrocarbon reservoirs is presented. This allows for the rapid evaluation and modeling of uncertainty for cross-fault fluid flow (e.g. via transmissibility multipliers). By utilising the fault property visualisation techniques presented, only a small number of scenarios need to be taken through to full reservoir flow simulation.

The natural variability of the input data and limited availability of local datasets often leads to the introduction of uncertain values or properties into fault seal workflows. The effect of these uncertainties on the results of a fault seal analysis is integral to the workflow presented here.

Measured fault rock property values from core samples are used to calibrate fault rock clay mixing/smearing and fault permeability predictors under for application to structural and stratigraphic models. Inaccuracies and uncertainties in both the input data and fault property prediction algorithms are incorporated. The ranking of probabilistic scenarios allows an improved understanding of the likely impact of reservoir cross-fault fluid flow, whilst at the same time allowing assessment of possible risk factors.

The fluid flow characteristics are assessed in terms of the fault hydraulic resistance and the effective cross-fault transmissibility (incorporating host cell properties). The impact of these different cross-fault fluid flow property distributions are presented by using streamlines. This visualisation technique allows for the rapid comparison of meaningful properties that can be compared across multiple uncertainty realisation models.

The rapid evaluation of multiple uncertainty realisation models means only the most appropriate, fully risked models need to be passed through to a full flow simulation.