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Assisted History-Matching for Fractured Reservoirs Characterization and Recovery Optimization using Connectivity Analysis

Arnaud Lange¹ and Alexandre De Lima²
¹IFP Energies nouvelles, Rueil-Malmaison, France
²UNICAMP, Rio de Janeiro, Brazil

It is estimated that 60% of the world's proven reserves reside in carbonate reservoirs for conventional oil, and that 90% of these reservoirs are fractured [16]. Fractures usually affect the production behavior and final recovery. The increasing number of mature fields where fractures caused unexpected production features gave rise to extensive efforts in better characterizing and integrating fracture properties in field-scale flow simulation models, for a correct production assessment and optimization [7]. Specific workflow and tools have been developed for fractured reservoir characterization in the past years [4]. In this workflow, (a) geologically-realistic models of the fault and fracture network are constructed from seismic, well and outcrop data [6], (b) the flow properties of these models are then characterized from dynamic field information (e.g. well tests, production data...) [19], (c) an equivalent simulation model applicable at reservoir scale is constructed thanks to appropriate flow up-scaling procedures [3][18], and (d) multiphase field production is simulated at reservoir scale with this equivalent model [17]. Using this workflow, reservoir-scale flow simulation models remain interpretable in geological terms, thus facilitating the understanding of the possible reservoir behaviors.

However the characterization of the flow properties of the geological fault/fracture network model, occuring at step (b), remains critical [13]. Indeed it requires to infer highly uncertain properties such as fracture length and/or fracture conductivity distribution from dynamic tests data, thus requiring accurate flow models directly applicable on geologically-realistic, e.g. multiscale fracture models. The associated computational cost limits the characterization to be performed through the calibration of local dynamic tests (flowmeters, well tests…), thus imposing a characterization strategy depending on fracture scale: (i) first the flow properties of multi-scale fracture networks are estimated from accurate flow models, but from local dynamic tests; (ii) large-scale fractures, i.e. that cannot be homogenized at reservoir-cell scale, are characterized from reservoir-scale production history simulations, that involve appropriate upscaled flow models with an explicit fault representation. Various inversion methodologies have been proposed for the local characterization of multiscale fracture networks from local flow data [13][5][14]. This paper presents an inversion methodology adapted to large-scale fault networks i.e. seismic and sub-seismic faults, via production history matching.


AAPG Search and Discovery Article #120034©2012 AAPG Hedberg Conference Fundamental Controls on Flow in Carbonates, Saint-Cyr Sur Mer, Provence, France, July 8-13, 2012