Rigorous Multi-Scenario Uncertainty Analysis: An Easy Way to Create anEnsemble of Many Concepts,with Hundreds of Uncertainties,and the Powerof the Cloud to Evaluate Thousands of Realizations in Hours

摘要

When key geological scenario uncertainties,captured in multiple conceptual models,are combined withcontinuous parameters,the evaluation of a representative sample set quickly becomes unmanageable,laborious and too time consuming to execute.A workflow is presented that enables users to easily modelconceptual as well as parametric uncertainties of the reservoir without the necessity of any complexscripting.The chain of models for all concepts is presented in one view,to provide overview of the keydifferences between concepts used.An ensemble of geologically sound samples can be created taking intoaccount parameter dependencies and probabilities of concepts.The chain of models per concept can easilybe (re)executed.A case study is presented that consists of multiple concepts based on different hierarchical stratigraphicmodels in combination with different fault models,each of which with its own fluid-(defined contacts percompartment),grid-(sub-layering and areal resolution) and rock property models.Volumetric calculationsare run on an ensemble to get static model observables like GRV,Pore Volume,Oil-In-Place,etc.,reportedby multiple sub-regions of the model in combination with a lease boundary.(When coupled with dynamicsimulation,observables like ultimate recovery,break-through timing,etc.could also be obtained).Asthousands of realizations were run concurrently,run time was reduced from weeks to hours.Results revealthe distribution and dependency of observables like GRV on top-structure-depth uncertainty and contact-level uncertainty.For in-place volumes the full suite of concepts and other parametric uncertainties includingthe stochastic uncertainties (i.e.seed) is analyzed.This also enables the identification of the key uncertaintiesthat impact equity the most,which can be of great commercial value during equity negotiations.Thisworkflow demonstrates how,with the power of Cloud computing,rigorous evaluation of multiple conceptscombined with many parametric uncertainties has been achieved within practical turn-around times.Assuch it overcomes the prohibitive hurdles of the past that often have led to simplifications necessary to savetime and effort.The result is better decision quality in resource development decisions.