WO2020047451A1 - Digitial multi-phase flow analysis system for assisting enhanced oil recovery - Google Patents

Abstract

Methods and systems for evaluating fluids in a hydrocarbon reservoir within heterogeneous formations are disclosed.

Description

DIGITAL MULTI-PHASE FLOW ANALYSIS SYSTEM FOR ASSISTING ENHANCED

OIL RECOVERY

CROSS REFERENCE PARAGRAPH

[0001] This application claims the benefit of U.S. Provisional Application No. 62/724921 , filed August 30, 2018, the disclosure of which is hereby incorporated herein by reference.

BACKGROUND

[0002] The disclosure generally relates to methods and systems for comparative evaluation and optimization of enhanced oil recovery (EOR) and improved oil recovery (IOR) development schemes in case of heterogeneous formation which combines digital rock approach with density functional modeling of processes at pore scale.

DESCRIPTION OF THE RELATED ART

[0003] One important part in hydrocarbon field development planning is evaluation and optimization of different enhanced or improved oil recovery schemes. At present this problem is solved by two complementary methods: (a) using detailed geological and hydrodynamic reservoir 3D modeling with application of commercial simulators to obtain quantitative description of reservoir processes, and (b) with physical core flood tests in a laboratory environment. Once a sufficient number of various development scenarios are obtained by ideally a combination of simulations and physical tests an ideal case is identified as the optimal development solution.

SUMMARY

[0004] Certain aspects of some embodiments disclosed herein are set forth below. It should be understood that these aspects are presented merely to provide the reader with a brief summary of certain forms the invention might take and that these aspects are not intended to limit the scope of the invention. Indeed, the invention may encompass a variety of aspects that may not be set forth below. [0005] The present disclosure includes any of the following embodiments in any combination(s) of one or more thereof:

[0006] According to an aspect of the present disclosure, one or more embodiments relate to a method for evaluating fluids in a hydrocarbon reservoir within a heterogeneous geological formation or a portion thereof, the method comprising: a) obtaining physical parameters of the fluids and the formation; b) constructing at least one three-dimensional (3D) model of the hydrocarbon reservoir using the physical parameters , wherein the three-dimensional model comprises simulations of pore structure and mineralogical content; c) calculating a hydrocarbon amount for each said three-dimensional model in step b); d) calculating overall amount of hydrocarbon reserves; and e) developing a completion plan based on the calculated overall hydrocarbon reserves.

[0007] In one embodiment, the physical parameters of the hydrocarbon reserves are obtained from fluid probes and certain physical properties located inside the hydrocarbon reservoir.

[0008] In one embodiment, the physical parameters include intrinsic properties, background properties, combined properties and artificially introduced components.

[0009] In one embodiment, the intrinsic properties include physical state of the produced hydrocarbon, composition and amount of formation water, mineralogy distribution in the formation, porosity distribution in the formation, and connectivity of pore structures in the formation.

[0010] In one embodiment, the background properties include pressure and temperature distribution in the formation.

[0011] In one embodiment, the combined properties include wettability distribution in the formation and absolute permeability distribution in the formation. [0012] In one embodiment, the artificially introduced components include secondary water and EOR Agents

[0013] In one embodiment, the physical parameters of the formation are obtained from samples of the formation.

[0014] In one embodiment, the processes are performed for a plurality of 3D models that aggregate to a portion of the hydrocarbon reservoir.

[0015] In one embodiment, the processes are performed for a plurality of deposits to evaluate an aggregate reserve by adding the overall hydrocarbon reserve of each of the deposits.

[0016] These together with other aspects, features, and advantages of the present disclosure, along with the various features of novelty, which characterize the invention, are pointed out with particularity in the claims annexed to and forming a part of this disclosure. The above aspects and advantages are neither exhaustive nor individually or jointly critical to the spirit or practice of the disclosure. Other aspects, features, and advantages of the present disclosure will become readily apparent to those skilled in the art from the following detailed description in combination with the accompanying drawings. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not restrictive.

[0017] This summary is provided to introduce a selection of concepts that are further described below in the detailed description. This summary is not intended to identify key or essential features of the claimed subject matter, nor is it intended to be used as an aid in limiting the scope of the claimed subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

[0018] FIG. 1 is an illustration of all relevant factors in simulating the rock formation - a representative reservoir element - for an EOR scheme. [0019] FIG. 2 shows an exemplary 3-dimensional representation of the simulated rock formation.

[0020] FIG. 3 shows an exemplary drainage relative permeability chart.

[0021] FIG. 4 is a flow diagram summarizing a method according to one embodiment.

[0022] The figures are not to scale. Wherever possible, the same reference numbers will be used throughout the drawing(s) and accompanying written description to refer to the same or like parts.

DETAILED DESCRIPTION

[0023] In the following description, numerous details are set forth to provide an understanding of some embodiments of the present disclosure. It is to be understood that the following disclosure provides many different embodiments, or examples, for implementing different features of various embodiments. Specific examples of components and arrangements are described below to simplify the disclosure. These are, of course, merely examples and are not intended to be limiting. In addition, the disclosure may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. Flowever, it will be understood by those of ordinary skill in the art that the system and/or methodology may be practiced without these details and that numerous variations or modifications from the described embodiments are possible. This description is not to be taken in a limiting sense, but rather made merely for the purpose of describing general principles of the implementations. The scope of the described implementations should be ascertained with reference to the issued claims.

[0024] As used herein, the terms“connect”,“connection”,“connected”,“in connection with”, and“connecting” are used to mean“in direct connection with” or“in connection with via one or more elements”; and the term“set” is used to mean“one element” or“more than one element”. Further, the terms“couple”,“coupling”,“coupled”,“coupled together”, and“coupled with” are used to mean“directly coupled together” or“coupled together via one or more elements”. As used herein, the terms "up" and "down"; "upper" and "lower"; "top" and "bottom"; and other like terms indicating relative positions to a given point or element are utilized to more clearly describe some elements. Commonly, these terms relate to a reference point at the surface from which drilling operations are initiated as being the top point and the total depth being the lowest point, wherein the well (e.g., wellbore, borehole) is vertical, horizontal or slanted relative to the surface.

[0025] As used herein, the term“tight hydrocarbon reservoir” is a reservoir containing hydrocarbons (such as oil and/or natural gas) that is formed of relatively impermeable reservoir rock from which hydrocarbon production is difficult. The relative impermeability of the reservoir rock can be caused by smaller grains or matrix between larger grains, or caused by predominant silt-sized or clay-sized grains (as is the case for tight shale reservoirs). Tight hydrocarbon reservoirs can contain oil and/or natural gas as well as water-based formation fluid such as brine in the relatively impermeable reservoir rock.

[0026] As used herein, the term “petrophysical properties” means physical and chemical properties of reservoir rock and its hydrocarbon content and non-hydrocarbon content, such as water-based formation fluids. As used herein,“formation” refers to an amount of rock strata that have a comparable lithology, facies or other similar properties. As used herein, “physical parameters” refer to measurable and quantifiable physical properties of rocks or fluids.

[0027] As used herein, a “completion plan” refers to the events and equipment necessary to bring a wellbore into production once drilling operations have been concluded, including but not limited to the assembly of downhole tubulars and equipment required to enable safe and efficient production from an oil or gas well.

[0028] Economic production from tight shale reservoirs (organic shale) is governed by the ability to position horizontal wells in a quality reservoir that can be effectively stimulated with hydraulic fracturing, using the log and core data acquired from vertical wells. The major factors that drive successful production from these wells include petrophysical properties, such as porosity, permeability, wettability, hydrocarbon saturation, and pore pressure. The same parameters affect production in other hydrocarbon reservoirs to varying degrees. Other factors include geo-mechanical attributes such as hydraulic fracture surface area plus fracture conductivity. In addition to accurately measuring all the physical and petrophysical properties of the reservoirs, it can be of equal importance to have accurate simulations based on known rock samples from hydrocarbon reservoirs. With accurate and realistic simulations, a completion plan can be developed to increase recovery efficiency.

[0029] Multi-phase flow analysis is used to set the rules for relative mobility of different fluids and phases in reservoir simulations by taking into consideration most if not all the relevant factors that are measurable about the hydrocarbon reservoir, including intrinsic properties, background properties, combined properties and the properties of the artificially introduced agents. For example, the intrinsic physical and petrophysical properties of the reservoirs, while also taking into consideration background properties such as the temperature distribution or pressure distributions. Other related factors include wettability distribution and absolute permeability distribution, as well as several artificially introduced factors such as secondary water, or the agents used in the EOR operation.

[0030] In addition to multi-phase flow analysis, digital rock modeling is performed for the hydrocarbon reservoir to evaluate the total amount of fluid in the reservoir. The digital rock modeling involves the combination of digital rock technology and density functional description of multi-phase multi-component mixtures. In the modeling, nanoscale digital rock models are used to compute the actual distribution of hydrocarbons in rock, which is then used to calculate the overall amount of the hydrocarbon reserves by taking into consideration the overall reservoir volume, the calculated amounts of hydrocarbon (oil or gas) for 3D models, and the relative frequency in the reservoir. [0031] Understanding of Multi-Phase Flow (MPF) phenomenon is the bedrock of planning and operating every displacement process in hydrocarbon recovery, including the challenging enhanced oil recovery (EOR) environment.

[0032] In many instances, companies do not have rock samples and/or special laboratory tests representing full rock heterogeneity, which will be dominant for the selected EOR process. The lack of complete rock samples makes it inherently difficult to develop optimal EOR processes. In some cases, companies wish to explore different scenarios while awaiting laboratory testing of the obtained rock samples. For these and other reasons, many EOR projects (and waterflood projects) are designed with limited guidance.

[0033] For example, it is known that certain EOR strategies are optimal for certain rock types, so knowing a rock type can specify a short list of potential EOR strategies. A typical reservoir, however, will have many rocks types, frequently as many as ten different rock types. These rock types may be in neighborhoods of varying size. In most cases, when EOR becomes relevant, the data necessary for specifying a useful EOR strategy does not exist because the full reservoir laboratory approach has not been performed. It may be known from core analysis that the reservoir contains ten different rock types, but the data is insufficient for determining how to apply the different EOR strategies that might be optimal for the known rock types to the reservoir as a whole.

[0034] Embodiments of the proposed disclosure provides a simulator to fill the gap existing in the development of EOR processes by providing a methodology to determine the MPF for all possible rock heterogeneities. The heterogeneity is based on information obtained using other known collecting methods. Once the simulation is completed, it can then be used for determining EOR decision points and EOR pilot design, as well as the interpretation of results. [0035] After the EOR design stage, one can have a much better understanding of the impact of the heterogeneity of the formation on incremental EOR potential of the reservoir and can properly initiate a well-focused core and lab investigation.

[0036] Fig. 1 is an illustration of factors to be considered in the design stage. Fig. 1 illustrates exemplary factors broken into intrinsic properties, background properties, and combined properties, as well as artificially introduced components for multi-phase flow simulation. As shown, the intrinsic properties include, but are not limited to, whether the hydrocarbon being produced is gas or oil, the composition and amount of formation water, the mineralogy distribution, the porosity distribution, and the connectivity of pore structures. Background properties include, but are not limited to, the pressure and temperature distribution. Combined properties include, for example, wettability distribution and absolute permeability distribution. Finally, artificially introduced components include, for example, secondary water, and EOR Agents.

[0037] In actual simulation, each factor may have a preset range for a user to choose from, as the ranges are mostly known from reservoir studies, especially from the studies where factors have similar physical and petrophysical characteristics.

[0038] In one embodiment, once the numerical ranges of different factors have been chosen, the simulator then builds synthetic rock models based on the chosen ranges. Of course, there are inherent relationships between the factors. For example, the gas/oil hydrocarbon is related to the temperature/pressure distribution, the pore structure and porosity distribution are related to absolute permeability distribution, etc. Taking all the known factors and their relationships together, a synthetic rock model can be obtained.

[0039] The simulation is run multiple times to obtain a series of equipossible synthetic rocks representing an envelope of valid treatments of the available data. The series of results are then composited together to obtain a 3-dimensional representation of the formation of interest, as shown in FIG. 2. The 3-dimensional representation can then be used to run a digital reservoir (DR) simulation for different parameters in synthetic MPF systems. For example, a“drainage relative permeability chart” as shown in Fig. 3 can be generated from the simulation results shown in Fig. 2. The user can generate different DR simulation for different sample or parameters.

[0040] After the MPF relationships are estimated for possible reservoir system, simulation results can be used in different scales for reservoir application. For example, at the micrometer level it can be used to study pore scale interaction (wettability). At the centimeter level it can be used for core displacement efficiency, well injectivity, and scaling up to well and formation impairment studies. At the meter-size level, it can be used to study formation heterogeneities or vertical sweep efficiency. At the hundred- meter level, it can be used to study geological heterogeneities and other operational challenges. Of course, with the increased scales, the cost and time for running the simulation will also increase.

[0041] The described simulation scheme provides more realistic rock properties and their spatial distribution within the formation. This facilitates better waterflood assessment when only limited rock data is available. The simulation scheme also enables EOR design with more representative heterogeneity and physics coverage, and better utilizes the geological and petrophysical facts that are already available. In addition, better rock simulation also results in faster EOR decision making.

[0042] Embodiments of the present disclosure provide a numerical system that enables the user to build multiple realizations of a reservoir rock using the range of petrophysical parameters and evaluate the impact of those parameters in different multi- phase flow environments. The present tool then enables the user to estimate a range of relative permeability and capillary pressure functions for various levels of displacements including a simple waterflood or rather complex chemical EOR displacement.

[0043] In an embodiment of the present disclosure, a proposed simulation using the MPF analysis is provided, wherein the simulation results suggest a better representation of actual well conditions. [0044] FIG. 4 is a flow diagram summarizing a method 400 according to one embodiment. At 402, a complete physical model of a reservoir or a representative portion of a reservoir is defined. The model is defined by first ascertaining and modeling the rock structure of the reservoir. Well logs and representative core samples are used to construct a digital model of neighborhoods of the reservoir corresponding to different rock types identified by combination of the well logs and representative core samples. The digital rock model is a table of numbers with three spatial dimensions, representing a full reservoir system digitally, as domain. The numbers represent physical attributes of voxels defined at locations of the reservoir represented by the three spatial dimensions of the table. The physical attributes can include porosity, pore structure and connectivity, content of various mineral types, and permeability functions for hydrocarbons and water. The digital rock model may be distributed according to methods used to analyze geology data. Different methods of characterizing core samples, for example, can give rise to different results. The digital rock model can be a distribution of sub-models, each based on one or more approaches to analyzing the reservoir data. The digital rock model can also be a mathematical combination of such sub-models, which may be linear, non-linear, weighted, or otherwise combined using factors or coefficients. The factors or coefficients may be weighting factors that determine the contribution of each sub-model to the overall model.

[0045] A chemical potential model is constructed representing the fluids in the reservoir. The chemical model is, or incorporates, a thermodynamic equation of state and provides chemical potentials for components of the fluids. The chemical potentials are used to compute phase behavior and compositions within the bulk fluids present in the reservoir.

[0046] Movement of components within the reservoir, i.e. through each voxel, is typically modelled using Darcy’s Law, and movements between the rock neighborhoods modeled in the digital rock model can be computed using transfer tensors. Porosity, pore throat size, fluid-fluid interactions, capillary pressure distribution, pore retention, capillary flow rates, and surface interactions can also be modeled in each voxel.

[0047] At 404, an enhanced recovery strategy is simulated using multiple versions of the physical model. As noted above, the multiple versions of the physical model may be based on different interpretations of the reservoir data used to build the physical model. The different interpretations may be based on different levels of confidence in conflicting results from different imaging methods, chemical analysis methods, log data, or the like. The different interpretations may also be based on different weightings applied to results from different analysis methods. The enhanced recovery strategy is typically implemented in the model by specifying time-series conditions of one or more voxels at the edge of the model space. Input of recovery fluids can be simulated as setting the condition and composition of one or more voxels to match the condition and composition of a fluid to be injected into the formation. The condition can be constant or can vary with time. Output can be simulated by setting the conditions of a boundary area of voxels to represent realistic formation outflow conditions. The model is then iterated to ascertain the evolution of multi-phase fluid flow through the modeled formation.

[0048] At 406, a range of possible outcomes, which provides estimated EOR potential from the reservoir for the tested EOR scheme, defined by the multiple versions of the physical model are determined. As noted above in connection with Fig. 3, the ensemble of models gives a distribution of results for a given enhanced recovery treatment, so the various possible outcomes of applying the treatment to the reservoir can be visualized. Some confidence can be gained about the range of possible outcomes and dependence on parameters of the enhanced recovery strategy, such as temperature, pressure, and composition, can be modeled.

[0049] The operations 402, 404, and 406 result in development of an envelope of EOR solutions based on digital rock analysis. One valuable outcome that can be modeled herein is total potential recovery of hydrocarbons from the reservoir. The total quantity of hydrocarbons in the reservoir can be estimated from the chemical potential model of the bulk fluids and phase interface and surface interaction in the reservoir. Use of a complete physical model that accounts for multi-phase fluid flow within the reservoir allows for total recovery to be estimated based on different enhanced recovery strategies and a range of total recovery volumes to be visualized. The envelope of EOR solutions can then be used to simulate various EOR operational designs and define a comparative development plan for the reservoir.

[0050] At 408, an operating window guidance is defined for an enhanced recovery operation based on the range of possible outcomes. For each possible outcome of interest, a tolerance can be defined, and parameters of the enhanced recovery strategy that most affect that outcome can be varied to model an operating window for the parameter. To the extent a parameter affects more than one possible outcome of interest, the operating window for the parameter can be defined from the operating window guidance to satisfy the tolerances for all possible outcomes to maximize chances of beneficial results when the strategy is applied to the reservoir. Weighting factors may be used to weight the effects of the different outcomes affected by the parameter of the strategy. For example, if bringing all versions of a first outcome of the strategy within tolerance requires a first limitation of a first parameter and bringing all versions of a second outcome of the strategy within tolerance requires a second limitation of the first parameter, where the second limitation is larger than the first limitation, such that the operating window of the first parameter is smaller when using the second limitation than when using the first limitation, the operating window can be defined by weighting the first and second limitations. Specifically, each of the first and second limitations can be diminished according to confidence in the likelihood of the outcome that drives the limitation. Using the example shown in Fig. 3, if the saturation figures returned by the model are unfavorable to some degree, pressures, temperatures, and water compositions can be adjusted, and the results modeled, to adjust the operating window of the strategy. [0051] The operating window guidance may implicate a control design. Where modeling indicates a particular outcome is sensitive to small changes in a parameter of the recovery strategy, a control design can be specified to prevent any unfavorable impacts from movement of the parameter. The control design may be defined to manage interactions of parameters, as well. Such interactions can be tested using the model, and the control design can be configured in advance to prevent combinations that might produce unwanted outcomes according to the model.

[0052] The control design may include particular equipment that can be provided to implement the control design. Examples include spare capacity for recovery operations, control valve turndown, and flow manifolding.

[0053] At 410, a contingency strategy is defined for the enhanced recovery operation based on the range of possible outcomes. The model results may show a possible outcome that cannot be satisfactorily managed, mitigated, or controlled by defining a suitable operating window or applying control. For example, one outcome may exhibit wide variation with model conditions based on the interpretations of reservoir data used to build the model. Such possibilities can be the subject of further contingencies that can be implemented in the event actual operation of the strategy in the reservoir results in model-suggested unfavorable results. Examples include additional containment of low or high vapor pressure materials, alternative processing equipment, unconventional subterranean treatments, and alternative transportation and storage.

[0054] At 412, the enhanced recovery operation is applied to the reservoir or portion of the reservoir to produce hydrocarbons from the reservoir. During application of the enhanced recovery operation, the model of the reservoir can be used to predict evolution of recovery performance based on production data. For example, actual production quantities of fluids and lift conditions can be provided to the model and updated results obtained to understand how reservoir operation might evolve. The likelihoods of contingencies being needed can be assessed, and any new contingencies can be identified and plans formulated to manage them.

[0055] The methods described herein can be used to test the impact of different permutations and combinations of EOR strategies in reservoirs having a plurality of rock types. Using these methods, different placements of EOR treatments in the reservoir can be studied, impacts of staging different EOR strategies can be studied, and combinations of EOR strategies delivered concurrently or sequentially to the reservoir as a whole or to parts of the reservoir can be studied. In such permutations and combinations, the impact of parameters of the EOR strategies can be evaluated to provide highly granular understanding of the behavior of fluids in the reservoir to guide EOR design and implementation.

[0056] Even though particular combinations of features are recited in the claims and/or disclosed in the specification, these combinations are not intended to limit the disclosure. In fact, many of these features may be combined in ways not specifically recited in the claims and/or disclosed in the specification. Although each dependent claim listed below may directly depend on only one other claim, the disclosure includes each dependent claim in combination with every other claim in the claim set.

[0057] Although the preceding description has been described herein with reference to particular means, materials and embodiments, it is not intended to be limited to the particulars disclosed herein; rather, it extends to all functionally equivalent structures, methods, and uses, such as are within the scope of the appended claims.

Claims

Claims:

1 . A method for evaluating fluids in a hydrocarbon reservoir within a heterogeneous geological formation or a portion thereof, the method comprising:

obtaining physical parameters of the fluids and the formation;

constructing a three-dimensional (3D) model of the hydrocarbon reservoir using the physical parameters, wherein the three-dimensional model comprises simulations of pore structure and mineralogical content;

calculating a hydrocarbon amount for the three-dimensional model;

calculating overall amount of hydrocarbon reserves in the formation; and creating a comparative development plan based on the calculated overall hydrocarbon reserves.

2. The method of claim 1 , wherein the physical parameters of the fluids are obtained from fluid probes located inside the hydrocarbon reservoir.

3. The method of claim 1 , wherein the physical parameters of the formation are obtained from samples of the formation.

4. The method of claim 1 , wherein the physical parameters comprise intrinsic properties, background properties, combined properties and artificially introduced components.

5. The method of claim 4, wherein the intrinsic properties comprise physical state of the produced hydrocarbon, composition and amount of formation water, mineralogy distribution in the formation, porosity distribution in the formation, and connectivity of pore structures in the formation.

6. The method of claim 4, wherein the background properties comprise pressure and temperature distribution in the formation.

7. The method of claim 4, wherein the combined properties comprise wettability distribution in the formation and absolute permeability distribution in the formation.

8. The method of claim 4, wherein the artificially introduced components comprise secondary water and enhanced recovery materials.

9. The method of claim 1 , wherein the 3D model is an ensemble model comprising a distribution of components based on different evaluations of data from the geologic formation.

10. The method of claim 9, wherein the completion plan includes a control design or a contingency based on possible outcomes provided by the 3D model.

11. The method of claim 1 , wherein the comparative development plan includes application of a plurality of enhanced recovery strategies to the reservoir.

12. A method for evaluating fluids in a hydrocarbon reservoir within a heterogeneous geological formation or a portion thereof, the method comprising:

obtaining physical parameters of the fluids and the formation;

constructing a three-dimensional (3D) model of the hydrocarbon reservoir using the physical parameters, wherein the three-dimensional model comprises simulations of pore structure and mineralogical content;

calculating a hydrocarbon amount for the three-dimensional model;

calculating overall amount of hydrocarbon reserves in the formation;

obtaining an operating window guidance for at least one enhanced recovery strategy from the 3D model;

defining an enhanced recovery operation based on the operating window guidance; and

applying the enhanced recovery operation to the hydrocarbon reservoir.

13. The method of claim 12, wherein obtaining the operating window guidance comprises using the 3D model to determine operating parameter impacts on reservoir performance, and defining the enhanced recovery operation comprises establishing an operating window for the parameters based on the operating window guidance.

14. The method of claim 13, wherein defining the enhanced recovery operation further comprises defining a control design based on the operating window guidance.

15. The method of claim 14, wherein defining the enhanced recovery operation further comprises defining a contingency plan from the operating window guidance.

16. A method of enhanced oil recovery, comprising:

constructing a physical model of a hydrocarbon reservoir from laboratory analyses of fluid and rock properties from core samples of the reservoir and from well logs, wherein the physical model is a 3D model ensemble of solutions based on different analyses of the fluid and rock properties and the well logs;

simulating a plurality of enhanced recovery strategies using the 3D model;

estimating a range of possible outcomes for each enhanced recovery strategy using the ensemble of solutions;

obtaining an operating window guidance for at least one enhanced recovery strategy using the 3D model; and

defining an enhanced recovery operation based on the operating window guidance.

17. The method of claim 16, further comprising applying the enhanced recovery operation to the hydrocarbon reservoir.

18. The method of claim 16, wherein obtaining the operating window guidance comprises using the 3D model to determine operating parameter impacts on reservoir performance, and defining the enhanced recovery operation comprises establishing an operating window for the parameters based on the operating window guidance.

19. The method of claim 18, wherein defining the enhanced recovery operation further comprises defining a control design based on the operating window guidance.

20. The method of claim 19, wherein defining the enhanced recovery operation further comprises defining a contingency plan from the operating window guidance.