With the increasing acceptance of stochastic workflows in mainstream reservoir engineering studies, many frameworks have been developed to assist in the history match of reservoir models. This paper describes the application of experimental design and response surface methods, not only in conditioning complex reservoir models to the historical production data but also in refining the reservoir models to improve the overall history match results. The reservoirs are in the Niger Delta and consist of faulted layers from both the Benin and Agbada formations. The reservoir models envelop all major reservoir uncertainties ranging from static parameters such as structure and porosity to dynamic parameters such as aquifer strength, relative permeability, and even production records. The experimental design combined all the subsurface uncertainties in different realizations and ensembles to construct response surface models capturing the multiple responses of the simulated historical performance. These response surface models serve three main purposes: identification of the "heavy hitters," improving the reservoir model, and facilitating the stochastic history match. The history-matched ensemble successfully explained the reservoir and drainage point production performance; identified uncertainties that have the most significant impact on the historical performance and development; established the most likely original water contact for one of the reservoir compartments; explained the connectivity between the different fault blocks; and formed the basis for risk mitigation analysis of further development in the reservoir. Introduction The usefulness of a model in supporting future development activities in a reservoir depends largely on how well the model is able to explain past reservoir production performance. This process, known as history match, involves conditioning a reservoir model to the historical production data. However, history match is not only a difficult problem; it is a non-unique and generally time-consuming inverse problem to solve. This non-uniqueness results in several combinations of model parameters that can adequately explain past reservoir performance. Though these models may satisfactorily explain past performance, they often produce divergent outcomes when used for predicting the future performance of the reservoir. This range of outcomes relates directly to the uncertainty associated with any development option and forms a critical input in business decisions. It is, therefore, desirable to have a method that both capture the widest possible combination of model parameters that explains historical production data and is quick to update. Considering the time intensive nature of history match and its other limitations, the traditional deterministic approach that relies on a trial-and-error method may be inappropriate in meeting these objectives. On the other hand, the process of stochastic history matching is different from conventional history matching and is more suited to handling uncertainties consistently. It involves creating a response surface model by fitting the outcomes of an experimental design to an equation containing the most influential parameters.
A North Oman Field producing from two stacked Cretaceous reservoirs characterized by variation in inter-particle porosity along with variable vuggular and fractured secondary porosity system was studied. The objective was to build a reliable DPDP reservoir static model with scarcely available key data. An interdisciplinary approach utilizing available data, supplemented with analogs was used to implement a hierarchically linked reservoir characterization and modeling workflow for the purpose dynamic flow simulation studies. In the absence of core data, the NMR T2 distribution and derived permeability scaled to well tests mobility were correlated with borehole image features in a key well to define a rock typing scheme. The saturation height function was developed directly from the Sw and resistivity logs, by transforming and adjusting NMR T2 distribution to saturation height. In wells with only conventional logs, the SHF was used to back-calculate permeability within the transition zone. Electrical image logs in horizontal wells were used to build a high-resolution layering framework extrapolated inter wells to model highly conductive features (vugs and fractures). To address a relationship between secondary porosity selectively seen in thin dense layers, a BHI-based layering along horizontal wells was used to build the reservoir stratigraphic correlation to capture vertical flow barriers and high permeability vuggy layers. This approach used textural characteristics of rocks together with production data to capture mechanical stratigraphic boundaries and enabled fracture density estimation per mechanical layer. Use of hierarchical modeling workflow enabled the use of available BHI based rock texture, VCL from computed logs and acoustic impedance from inverted 3D seismic data to build 3D probability cubes of "mud-supported" and "grain-supported" rock textures. Conditioned to those 3D textural trend models, some seismic attributes were used as a guide to stochastically model the distribution of rock fabric based on the Lucia classification and the related inter-granular porosity. Subsequently the 3D distribution of Lucia-based Permeability and SW properties were also developed. Based on the assumption that fractures are developed within the perturbed stress field caused by the activity of the main pre-existing faults, a geomechanically-based process NFP workflow enabled us to build reservoir-scale fracture models. This workflow integrated seismic scale faults, and the distribution of fracture geometry and density from the wells coming from BHI logs, together with seismic discontinuity planes extracted from frequency-based filtering of seismic structural attributes. The tectonic model boundary conditions were estimated using 1D geomechanical models and analog data from neighboring fields. NFP-workflow generated fracture drivers; together with other fracture parameters, estimated from analog fields, neighboring outcrops and open literature, which were used to build a 3D multi-scale hybrid fracture model of the reservoir. The DPDP static reservoir model allowed dynamic history matching of the field with only global parameter adjustments, thus validating the property distribution from this static model.
Introduction: The North Kuwait Jurassic Complex (NKJC) is composed of six fields and situated in the Northern part of Kuwait (Figure 1). The field is characterized by dual porosity/permeability in deep HP/HT conditions, with wide variety of hydrocarbon fluids ranging from volatile oil to gas condensate. The primary recovery mechanism and the recovery efficiency strongly rely on fractures. Therefore, reliable and calibrated fracture model is required in getting a representative dynamic model. Using a wide range of 2D/3D seismic, geometrical and petrophysical attributes, a hybrid natural fractured reservoir static geomodel, made of Discrete Fracture Network (DFN) and Implict Fracture model (IFM), has enabled a reasonable 3D representation of three sets of fractures, identified based on well and seismic data:Fracture corridors associated to geophysically interpreted faults;Medium scale layer bound geomechanically controlled fractures; andFolding related fractures. The new hybrid fracture model was calibrated using PLT, MDT and PBU data from more than 60 wells drilled in the reservoir. This paper demonstrates how a calibrated hybrid fracture model has shortened the process of the history match significantly, which required only very small adjustments/alterations to the initial static model. The uncertainty and the challenges faced while calibrating the model were addressed, together with the highly sensitive parameters that were adjusted to match the dynamic data. Succeeding a smooth and timely history match resulted in significant CPU time gain, and an optimized well count that went into the Asset Action Plan.
As Kuwait focuses on developing the deep Jurassic reservoirs, the Gotnia Formation presents significant drilling challenges. It is the regional seal, consisting of alternating Salt and Anhydrite cycles, with over-pressured carbonate streaks, which are also targets for future exploration. The objective of this study was to unravel the Gotnia architecture, through detailed mapping of the intermediate cycles, mitigating drilling risks and characterizing the carbonate reservoirs. A combination of noise attenuation, bandwidth extension and seismic adaptive wavelet processing (SAWP)) was applied on the seismic data, to improve the signal-to-noise ratio of the seismic data between 50Hz to 70Hz and therefore reveal the Anhydrite cycles, which house the carbonate streaks. The Salt-Anhydrite cycles were correlated, using Triple Combo and Elastic logs, in seventy-six wells, and spatially interpreted on the band-limited P-impedance volume, generated through pre-stack inversion. Pinched out cycles were identified by integrating mud logs with seismic data and depositional trends. Pre-stack stochastic inversion was performed to map the thin carbonate streaks and characterize the carbonate reservoirs. The improved seismic resolution resulted in superior results compared to the legacy cube and aided in enhancing the reflector continuity of Salt-Anhydrite cycles. In corroboration with the well data, three cycles of alternating salt and anhydrite, with varying thickness, were mapped. These cycles showed a distinctive impedance contrast and were noticeably more visible on the P-impedance volume, compared to the seismic amplitude volume. The second Anhydrite cycle was missing in some wells and the lateral extension of the pinch-outs was interpreted and validated based on the P-impedance volume. As the carbonate streaks were beyond the seismic resolution, they were not visible on the Deterministic P-impedance. The amount of thin carbonate streaks within the Anhydrite cycles could be qualitatively assessed based on the impedance values of the entire zone. Areas, within the zone, with a higher number of and more porous carbonate streaks displayed lowering of the overall impedance values in the Anhydrite zones, and could pose drilling risks. This information was used to guide the pre-stack stochastic inversion to populate the thin carbonate streaks and generate a high-resolution facies volume, through Bayesian Classification. Through this study, the expected cycles and over-pressured carbonate layers in the Gotnia formation were predicted, which can be used to plan and manage the drilling risks and reduce operational costs. This study presents an integrated and iterative approach to interpretation, where the well log analysis, seismic inversion and horizon interpretation were done in parallel, to develop a better understanding of the sub-surface. This workflow will be especially useful for interpretation of over-pressured overburden zones or cap rocks, where the available log data can be limited.
A hybrid natural fractured reservoir static geomodel using a wide range of 2D/3D seismic, geometrical and petrophysical attributes has enabled a reasonable 3D representation of three sets of fractures in the SA field, part of North Kuwait Jurassic Complex (NKJC). Based on well and seismic data, the three sets are fracture corridors associated with geophysically interpreted faults; medium scale layer-bound geomechanically controlled fractures; and folding-related fractures. The new hybrid fracture model, which is made of a discrete fracture network (DFN) and an implict fracture model (IFM), was calibrated using production logging tool (PLT), modular formation dynamics tester (MDT), and pressure buildup (PBU) data from 27 wells. The calibrated hybrid fracture model has shortened the process of the history match significantly, requiring only very small adjustments/alterations to the initial static model. Achieving a smooth and timely history match resulted in significant CPU time gain and an optimized well count that went into the Asset Action Plan.
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