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This field case present a risk analysis on production, plateau duration and ultimate recovery factor performed on a fractured carbonate reservoir. The field has been under early production for more than 48 years, with less than 2% cumulative produced Oil. Historical data measurements on Well Production Oil Rate, Well Gas Oil Ratio (GOR), Well Static Pressure and Well Bottom Hole Flowing Pressure have been utilized in order to constrain uncertain parameters during historical period and then propagate into prediction. The risk analysis takes into account reservoir uncertainties and geological uncertainties on Discrete Fracture Network (DFN). Several surface/controllable parameters have been considered for the Risk analysis evaluation on Plateau Length hypothesis and Recovery Factor. The risk analysis accounts for two main recovery mechanisms: gas injection from the crest for Gas gravity drainage and periphery down dip water injection with imbibition. Several scenarios of DFN's and 43 uncertain reservoir parameters with probability distribution were considered. Experimental Design and Response Surface Methodology have been extensively applied to minimize the number of Reservoir simulation runs of the study. Plackett and Burman Experimental Design has been used for the Screening Phase. During the screening phase, it has been revealed that 7 uncertain parameters account for more than 80 % of the total variation of Cumulative Oil Production. A detailed Latin Hypercube has been performed with 3 discrete fracture network, controllable uncertain parameters and these 7 most relevant parameters. This risk analysis identified the best cases of each phase of the development, P10 and P90, and the major uncertainties impacting the field development plan. Mitigation, acquisition and monitoring plan have been defined accordingly to reduce the major impacting uncertainties.
This field case present a risk analysis on production, plateau duration and ultimate recovery factor performed on a fractured carbonate reservoir. The field has been under early production for more than 48 years, with less than 2% cumulative produced Oil. Historical data measurements on Well Production Oil Rate, Well Gas Oil Ratio (GOR), Well Static Pressure and Well Bottom Hole Flowing Pressure have been utilized in order to constrain uncertain parameters during historical period and then propagate into prediction. The risk analysis takes into account reservoir uncertainties and geological uncertainties on Discrete Fracture Network (DFN). Several surface/controllable parameters have been considered for the Risk analysis evaluation on Plateau Length hypothesis and Recovery Factor. The risk analysis accounts for two main recovery mechanisms: gas injection from the crest for Gas gravity drainage and periphery down dip water injection with imbibition. Several scenarios of DFN's and 43 uncertain reservoir parameters with probability distribution were considered. Experimental Design and Response Surface Methodology have been extensively applied to minimize the number of Reservoir simulation runs of the study. Plackett and Burman Experimental Design has been used for the Screening Phase. During the screening phase, it has been revealed that 7 uncertain parameters account for more than 80 % of the total variation of Cumulative Oil Production. A detailed Latin Hypercube has been performed with 3 discrete fracture network, controllable uncertain parameters and these 7 most relevant parameters. This risk analysis identified the best cases of each phase of the development, P10 and P90, and the major uncertainties impacting the field development plan. Mitigation, acquisition and monitoring plan have been defined accordingly to reduce the major impacting uncertainties.
Uncertainty analysis using experimental design and response surface techniques has been extensively used in the field of reservoir simulation. This study outlines an innovative workflow to generate multiple realizations of forward stratigraphic modelling of three Lower Cretaceous reservoirs from onshore Abu Dhabi. Forward stratigraphic modelling is a deterministic technique that simulates basin infill providing a better understanding of vertical and lateral facies distribution and connectivity in sedimentary basins. During the course of forward modelling a variety of environmental and stratigraphic parameters are used. Due to the uncertainties of these parameters it is critical to assess their impact on the development of the basin fill. The experimental design and response surface techniques have been innovatively applied at reservoir scale to enhance the understanding of major controlling parameters on carbonate production and to produce alternative facies distribution scenarios in the study reservoirs. The methodology used in this study was based on running multiple simulations, through varying key input parameters. The best stratigraphic models were then selected based on calibration quality and geological consistency. Calibration quality was assessed by two user defined quantitative functions called Thickness Calibration Indicator and Rock Texture Calibration Indicator. The initial step in the workflow identified uncertain environmental parameters (e.g. eustasy, carbonate production versus depth, carbonate production versus time, wave parameters, gravity and wave transport and erosion rates) from a manually calibrated reference case and ranges of values for each parameter defined based on the knowledge of geology over the area. Latin Hypercube experimental design was then used to define a set of simulations to allow an efficient and uniform sampling of the entire uncertain domain. Sensitivity analysis was then performed on simulation responses (texture and thickness calibration indicators) using the technique of nonparametric Response Surface Modelling (RSM). The influence (quantitative and qualitative) of the impacting parameters on responses was studied to identify the most influential parameters as well as the ranges yielding good calibration indicator values. A further set of simulations was then launched that considered the most influential parameters and their precise ranges. Non critical parameters were assigned with the constant values from the reference case model. These simulations generated a series of well calibrated models. A filtering of simulations with high calibration indicator values and good geological consistency was then performed to choose acceptable multi-realizations. Finally, thickness and texture confidence properties were mapped based on the selected multi-realizations and the reference case. Sensitivity study on three Lower Cretaceous reservoirs from onshore Abu Dhabi successfully addressed the uncertainty associated with forward stratigraphic model input parameters. Sensitivity analysis was performed using Experimental Design and RSM. This was applied to enhance the understanding of the major controlling environmental parameters on carbonate production for individual sequence with each of the study reservoirs.
Naturally fractured reservoirs are indescribable systems to characterize and difficult to produce and forecast. For the development of such reservoirs, the role of naturally forming fractures in the different development stages needs to be recognized, especially for the pressure maintenance and enhanced oil recovery stages. Recent development in the field of naturally carbonate fractured aimed at fracture characterization, fracture modeling, and fracture network impact of fracture networks on oil recovery were reviewed. Consequently, fracture identification and characterization played pivotal roles in understanding production mechanisms by integrating multiple geosciences sources and reservoir engineering data. In addition, a realistic fracture modeling approach, such as a hybrid, can provide a more accurate representation of the behavior of the fracture and, hence, a more realistic reservoir model for reservoir production and management. In this respect, the influence of different fracture types present in the reservoir, such as major, medium, minor, and hairline fractures networks, and their orientations were found to have different rules and impacts on oil production in the primary, secondary, and EOR stages. In addition, any simplification or homogenization of the fracture types might end in over or underestimating the oil recovery. Improved fracture network modeling requires numerous considerations, such as data collection, facture characterization, reservoir simulation, model calibration, and model updating based on newly acquired field data are essential for improved fracture network description. Hence, integrating multiple techniques and data sources is recommended for obtaining a reliable reservoir model for optimizing the primary and enhanced oil recovery methods.
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