Efficient Optimization and Uncertainty Analysis of Field Development Strategies by Incorporating Economic Decisions in Reservoir Simulation Models

2020 ◽  
Author(s):  
James Browning ◽  
Sheldon Gorell ◽  
Justin Andrews
Keyword(s):  
Uncertainty Analysis ◽  
Reservoir Simulation ◽  
Simulation Models ◽  
Development Strategies ◽  
Field Development ◽  
Economic Decisions

Incorporating Economic Decisions into Reservoir Simulation to Support Accurate and Efficient Optimization and Analysis of Field Development Strategies

2021 ◽  
Author(s):  
Jim Browning ◽  
Sheldon Gorell
Keyword(s):  
Reservoir Simulation ◽  
Value Added ◽  
Simulation Models ◽  
Operating Conditions ◽  
Conditional Logic ◽  
Economic Optimization ◽  
Field Development ◽  
Production Constraints ◽  
Automated Method ◽  
Economic Decision Making

Abstract Economic optimization of a reservoir can be extremely tedious and time consuming. It is particularly difficult with many wells, some of which can become non-economic within the simulated time period. These problems can be mitigated by: 1) analyzing the results of a simulation once it has run, or 2) applying injection or production constraints at the well level. An example of option 1 would be integration with a spreadsheet or economic simulation package after the simulation has run. An example of option 2 would be to set a maximum water cut, upon which the well constraints could be changed, or the well could be shut in within the simulation. Both of these methods have drawbacks. If the goal is to account for how changes in a well operating strategy affects other wells, then analysis after the fact requires many runs to sequentially identify and modify well constraints at the correct times and in the correct order. In contrast, applying injection and production constraints to wells is not the same as applying true economic constraints. The objective of this work was to develop an automated method which includes economic considerations within the simulator to decrease the amount of time optimizing a single model and allows more time to analyze uncertainty within the economic decision making process. This study developed automated methods and procedures to include economic calculations within the context of a standard reservoir simulation. The method utilized modifications to available conditional logic features to internally include and export key economic metrics to support appropriate automatic field development changes. This method was tested using synthetic models with different amounts of wells and operating conditions. It was validated using after the fact calculations on a well by well basis to confirm the process. People costs are always among the most significant associated with running a business. Therefore, it is imperative for people to be as efficient and productive as possible. The method presented in this study significantly reduces the amount of time and effort associated with tedious and manual manipulations of simulation models. These savings enable an organization to focus on more value-added activities including, but not limited to, accurately optimizing and estimating of uncertainty associated decisions supported by reservoir simulation.

Devising and Optimizing Development Strategies for South Fuwaris Field Using Integrated Reservoir Simulation Models

2015 ◽  
Author(s):  
Ahmad Al-Aruri ◽  
Majed Al-Suwailem ◽  
Saud Al-Otaibi ◽  
Saleh Al-Mutairi ◽  
Kris Pederson ◽  
...  
Keyword(s):  
Reservoir Simulation ◽  
Simulation Models ◽  
Development Strategies

A Methodology To Reduce Uncertainty Constrained to Observed Data

2009 ◽  
Vol 12 (01) ◽  
pp. 167-180 ◽  
Author(s):  
Célio Maschio ◽  
Denis J. Schiozer ◽  
Marcos A.B. de Moura Filho ◽  
Gustavo G. Becerra
Keyword(s):  
Uncertainty Analysis ◽  
Reservoir Simulation ◽  
History Matching ◽  
Simulation Models ◽  
Natural Manner ◽  
Realistic Case ◽  
The Third ◽  
Campos Basin ◽  
Attribute Levels ◽  
Integrated Study

Summary This paper presents a new methodology to deal with uncertainty mitigation by using observed data, integrating the uncertainty analysis, and the history matching processes. The proposed methods are robust and easy to use, and offer an alternative to traditional history matching methodologies. The main characteristic of the methodology is the use of observed data as constraints to reduce the uncertainty of the reservoir parameters. The main objective is the integration of uncertainty analysis with history matching, providing a natural manner to make predictions under reduced uncertainty. Three methods are proposed:probability redistribution,elimination of attribute levels, andredefinition of attribute values. To test the results of the proposed approach, we investigated three reservoir examples. The first one is a synthetic and simple case; the second one is a synthetic but realistic case; and the third one is a real reservoir from the Campos basin of Brazil. The results presented in the paper show that it is possible to conduct an integrated study of uncertainty analysis and history matching. The main contribution of this work is to present a practical way to increase the reliability of prediction through reservoir simulation models that incorporate uncertainty analysis in the history period and provide reliable reservoir-simulation models for prediction forecast.

The Geochemical Survey Methods for Optimization of Oil Field Development

2021 ◽  
Author(s):  
Maria Sergeevna Shipaeva ◽  
Danis Karlovich Nurgaliev ◽  
Vladislav Anatolevich Sudakov ◽  
Artur Albertovich Shakirov ◽  
Azat Abuzarovich Lutfullin ◽  
...  
Keyword(s):  
Flow Rate ◽  
Reservoir Simulation ◽  
Produced Water ◽  
Survey Methods ◽  
Simulation Models ◽  
Oil Field ◽  
Geochemical Composition ◽  
Field Development ◽  
Water Composition ◽  
The Impact

Abstract The paper considers issues of determining the direction of filtration for oil deposits by means of complex study of the geochemical composition of formation fluids and the dynamics of bottomhole pressure and flow rates, and further use of this information in geological and reservoir simulation models. This integrated technology is not expensive and makes it possible to identify geological uncertainties in the reservoir for intelligent management of development processes, such as waterflooding optimization, reservoir simulation models improvement, water cut source definition, etc. Improving the reliability of information about the reservoir and the presented fluids is undoubtedly relevant and significant task. To solve this problem, fluid samples were taken and complex studies of the composition of the produced water was carried out, including the determination of hydrogen and oxygen isotopes and element composition. The authors note that the isotopic composition of formation waters for a number of wells differs from the analogical parameters for injected water, which is probably associated with the area of ​​uneven reservoir distribution and the existence of a stagnant undrained zone. The result of the calculations is an estimate of the impact coefficient of the injected water on the water composition in the surrounding producer wells. In addition to this, the work included the analysis of the dynamics of fluid flow rate, oil flow rate, bottomhole and reservoir pressures, the influence of injection on the pressure in the drainage area of ​​producer wells. Basing on the results obtained the recommendations were given for changing the injection patterns as it is noted that a number of wells are not affected by injection. Recommendations have been developed for carrying out workovers in order to prevent a decrease in pressure and an increase in oil production.

scholarly journals Developing a workflow to represent fractured carbonate reservoirs for simulation models under uncertainties based on flow unit concept

2019 ◽  
Vol 74 ◽  
pp. 15 ◽  
Author(s):  
Seyed Kourosh Mahjour ◽  
Manuel Gomes Correia ◽  
Antonio Alberto de Souza dos Santos ◽  
Denis José Schiozer
Keyword(s):  
Uncertainty Analysis ◽  
Reservoir Simulation ◽  
Reference Model ◽  
Simulation Models ◽  
Development Planning ◽  
Reservoir Rock ◽  
Geostatistical Modeling ◽  
Flow Units ◽  
Uncertainty Space ◽  
Fractured Carbonate

Description of fractured reservoir rock under uncertainties in a 3D model and integration with reservoir simulation is still a challenging topic. In particular, mapping the potential zones with a reservoir quality can be very useful for making decisions and support development planning. This mapping can be done through the concept of flow units. In this paper, an integrated approach including a Hierarchical Cluster Analysis (HCA), geostatistical modeling and uncertainty analysis is developed and applied to a fractured carbonate in order to integrate on numerical simulation. The workflow begins with different HCA methods, performed to well-logs in three wells, to identify flow units and rock types. Geostatistical techniques are then applied to extend the flow units, petrophysical properties and fractures into the inter-well area. Finally, uncertainty analysis is applied to combine different types of uncertainties for generating ensemble reservoir simulation models. The obtained clusters from different HCA methods are evaluated by the cophenetic coefficient, correlation coefficient, and variation coefficient, and the most appropriate clustering method is used to identify flow units for geostatistical modeling. We subsequently define uncertainties for static and dynamic properties such as permeability, porosity, net-to-gross, fracture, water-relative permeability, fluid properties, and rock compressibility. Discretized Latin Hypercube with Geostatistical (DLHG) method is applied to combine the defined uncertainties and create an ensemble of 200 simulation models which can span the uncertainty space. Eventually, a base production strategy is defined under operational conditions to check the consistency and reliability of the models created with UNISIM-II-R (reference model) as a real reservoir with known results. Results represent the compatibility of the methodology to characterize fractured reservoirs since those models are consistent with the reference model (used to generate the simulation models). The proposed workflow provides an efficient and useful means of supporting development planning under uncertainty.

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