Reservoir Zonation - A Novel Approach: Use of Core Derived K-Ø-Swirr Relationship to Define Reservoir Rock Types (RRTs)

摘要

Rock typing is an essential reservoir characterization tool to reflect the spatial variation in initial fluidrndistribution and flow behavior characteristics. Rock typing techniques are generally based on porositypermeabilityrnrelationships to establish the types of rocks present in the reservoir. These techniques lackrnin effective segregation of reservoir into definite number of zones/rock-types with clear boundaries. Thisrnresults in a non-unique rock-typing scheme with arbitrary number of RRTs depending on data manipulation.rnMoreover, these RRTs do not correspond to separate J-function curves due to negligence to waterrnsaturation term. To overcome these problems, a new approach for reservoir zonation is developed whichrnhas been tested in a few off-shore sandstone reservoirs.rnThis paper illustrates a robust method of rock typing using a new theoretical development andrnmathematical formulation. The method integrates irreducible water saturation term with modified Carmen-rnKozney equation using a proposed pore-throat dependent water saturation function [S_(wirr) = exprn(-ar~t)]. The generalized porosity-permeability-saturation equation [K = AØ~3(lnS_(wirr))~B] thus derived isrnfitted on the Routine Core Analysis (RCAL) data for division of reservoir section into different layersrnhaving unique coefficient-exponent set (A, B) representing RRTs.rnApplication of this method resulted in an effective RRT scheme as evident from the unique coefficientexponentrnsets as well as separate J-function curves. The unique porosity-permeability-saturation relationshiprnexisting for each RRT has been thus obtained from the RCAL data. This relationship can be used asrnan efficient tool for reservoir zonation. Reservoir zonation algorithm, analysis results and validationrnprocedures are discussed using field examples.rnReservoir characterization is the key to improve reservoir performance prediction and recoveryrnoptimization. This paper presents a novel approach to effectively segregate the reservoir into definiternnumber of RRTs using only RCAL data. This work also presents a theoretically derived K-Ø-Swirrrnrelationship based on pore scale attributes. Irreducible water saturation, being an eminent parameterrndescribing the internal architecture of the rock, is included in formulation and derivation of a theoreticalrnframework to address classification of RRTs.