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Abstract A flow simulation-driven time-lapse seismic feasibility study is performed for the Amberjack field that leverages existing multi-vintage 4D time-lapse seismic data. The focus is a field consisting of stacked shelf and deepwater reservoir sands situated in the Gulf of Mexico in Mississippi Canyon Block 109 in 1,030 ft of water. The solution leverages seismic interpretation, seismic inversion, earth modeling, and reservoir simulation [including embedded petro-elastic modeling (PEM) capabilities] to enable the reconciliation of data across multiple seismic vintages and forecast the optimal future seismic survey acquisition in a closed-loop. The overarching feasibility solution is integrated and simulation-driven involving multi-vintage seismic inversion, spatially constraining the petrophysical property model by seismic inversion, and performing reservoir simulation with the embedded PEM. The PEM is used to compute P-impedance and Vp/Vs dynamically, which enables tuning to both historical production and multi-vintage seismic data. The process considers a hybrid fine-scale 3D geocellular model in which the only upscaling of petrophysical properties occurs when the P-impedance from seismic inversion is blocked to the 3D geocellular grid. This process minimizes resampling errors and promotes direct tuning of the simulator response with registered seismic that has been blocked to a geocellular earth model grid. The results illustrate a three-part simulation-to-seismic calibration procedure that culminates with a prediction step which leads to a simulation-proposed time-lapse seismic acquisition timeline that is consistent with the calibrated reservoir simulation model. The first calibration tunes the model to historical production profiles. The second calibration reconciles the dynamic P-impedance estimate of the simulated shallow reservoir with that of the seismic inversion blocked to the 3D geocellular grid. The combination of these two steps outline a seismic-driven history matching process whereby the simulation model is not only consistent with production data but also the subsurface geologic and fluid saturation description. Large and short wavelength disparities in the P-impedance calibration existing between the simulator response and the time-lapse seismic data are attributed to resampling errors as a result of seismic inversion-derived P-impedance being blocked to the 3D geocelluar grid, as well as sparse well control in the earth model which leads to the obscuring of some asset-specific characteristics. The results of the third calibration step show how the time-lapse seismic feasibility solution accurately confirms prior seismic surveys undertaken in the asset. Given this confirmation, the solution achieves a suitable prediction of seismic-derived rock property response from the reservoir simulator as well as the optimal future time-lapse seismic acquisition time.
ABSTRACT Integrated time-lapse solutions involve maintaining or establishing interpretive continuity between determined multi-vintage rock properties from seismic inversion and simulated fluid production. To achieve this continuity, the solution incorporates a petro-elastic model (PEM) that depends on select dry rock property descriptions from cores or reference descriptions. Because of operational costs and/or time constraints, it is often not possible to adequately acquire this data, which results in a small data challenge. An integrated rock typing and metaheuristic optimization technique are combined to form a small data engine that completes an ill-posed petro-elastic characterization for a PEM embedded within a reservoir simulator. The value of rock typing helps expedite the metaheuristic optimization process, diminishing the need for stochastic computation. Presentation Date: Wednesday, September 18, 2019 Session Start Time: 9:20 AM Presentation Time: 11:25 AM Location: Poster Station 13 Presentation Type: Poster
Abstract Multi-rock type cores can be characterized by complex higher order connectivity relationships within an agglomerated petrophysical system. A solution that relates multiphase flow simulation in cores to time-lapse seismic properties in order to examine closed-loop 4D integration is performed at a high level on a plug. While a 4D workflow is not explicitly examined in this work, the requisite petro-elastic modeling (PEM) method based on a simulation-driven interpretation of the Gassmann equation is described and a comparison is made with its empirically derived counterpart. This work illustrates that a simulation-driven petro-elastic modeling approach can be used to generate time-dependent saturated rock properties consistent with seismic attribute description at the plug and core scales. The results demonstrate the simulation-driven approach, of a petro-elastic model embedded in a reservoir simulator, as an alternative to relating pressure and saturation from reservoir simulator-to-seismic-derived properties using a priori empirically based correlations. The method discussed in this paper maintains appreciable continuity with the results of empirically based petro-elastic methods but demonstrates differences commensurate with principal fluid differentiation capability inherent to reservoir simulator-derived data and observed time-lapse seismic response. The significance of applied multi-porosity relationships is further realized upon examination of the time-dependent petro-elastic model results.
Abstract The petro-elastic model (PEM) represents an integral component in the closed-loop calibration of integrated four-dimensional (4D) solutions incorporating time-lapse seismic, elastic and petrophysical rock property modeling, and reservoir simulation. Calibration of the reservoir simulation model is needed so that it is not only consistent with production history but also with the contemporaneous subsurface description as characterized by time-lapse seismic. The PEM requires dry rock properties in its description, which are typically derived from mechanical rock tests. In the absence of those mechanical tests, a small data challenge is posed, whereby all necessary data is not available but the value of reconciling seismic attributes to simulated production remains. A seismic inversion-constrained n-dimensional metaheuristic optimization technique is employed directly on three-dimensional (3D) geocellular arrays to determine elastic and density properties for the PEM embedded in the commercial reservoir simulator. Ill-posed dry elastic and density property models are considered in a field case where the seismic inversion and petrophysical property model constrained by seismic inversion exist. An n-dimensional design optimization technique is implemented to determine the optimal solution of a multidimensional pseudo-objective function comprised of multidimensional design variables. This study investigates the execution of a modified particle swarm optimization (PSO) method combined with an exterior penalty function (EPF) with varied constraints. The proposed technique involves using n-dimensional design optimization to solve the pseudo-objective function comprised of the PSO and EPF given limited availability of constraints. In this work, an examination of heavily and reduced-order penalized metaheuristic optimization processes, where the design variables and optimal solution are derived from 3D arrays, is conducted so that constraint applicability is quantified. While the process is examined specifically for PEM, it can be applied to other data-limited modeling techniques.
Abstract A rock-physics-based evaluation of elastic properties is examined in a coal core, using a three-dimensional (3D) reservoir simulator with an embedded petro-elastic model (PEM) to facilitate the evaluation of fracture productivity mechanisms. The analysis expedites what-if scenario evaluation at reduced costs compared to laboratory experimentation. The flow rates and capillary pressure are incorporated into a simulated coreflood to assess the effect of production on elastic properties at the core scale. A simulated coreflood is performed using an automated steady-state fractional flow process for mixed rock-type systems, which was developed as part of a process automation controller for a reservoir simulator. The process automation promotes adherence to established laboratory-based coreflooding procedures while optimizing for work process efficiency. Typical steady-state modeling processes are characterized as occurring in the capillary limit (CL) or viscous limit (VL) conditions, which are differentiated by flow velocity and capillary equilibration. The elastic properties are calculated by the reservoir simulator during the simulation, based on two available petro-elastic modeling methods—one semi-empirical and the other explicit, based on simulator parameters. The impact of flow rate, capillary pressure, and production on the elastic properties of a coal core are evaluated by simulated primary imbibition coreflooding with application to coal bed methane (CBM) production. The elastic properties are analyzed directly while also considering a dimensionless elastic property formulation. This dimensionless determination amplifies changes in elastic properties that might not otherwise be observed in the results directly; additionally, it combines spatial and temporal changes into an amalgamated variable. In addition to the spatio-temporal characterization of the dimensionless solution, results also show that it is consistent with the pressure solution over a given interval of simulated time. Differences in simulated coreflooding results are observed, which are driven by disparate flow regimes and applied capillary pressure. The differences are attributed to the CL condition imbibition coreflooding results showing decreased affinity to the wetting phase compared to VL-based simulation results. The flow component of the digital coreflooding results is considered valuable to overall asset productivity management. The evolution of simulated elastic properties in the digital core similarly shows that changes in saturated rock properties develop with specific flow conditions and highlights potential uses for core scale analysis in fracture productivity assessment.