Approach for Full Field Scale Smart Well Modeling and Optimization (Russian)

2011 ◽  
Author(s):  
Alexey Andreevich Khrulenko ◽  
Anatoly B. Zolotukhin
Keyword(s):  
Field Scale ◽  
Full Field ◽  
Modeling And Optimization

Approach for Full Field Scale Smart Well Modeling and Optimization

2011 ◽  
Author(s):  
Alexey Andreevich Khrulenko ◽  
Anatoly B. Zolotukhin
Keyword(s):  
Field Scale ◽  
Full Field ◽  
Modeling And Optimization

Practical Upscaling of Immiscible WAG Hysteresis Parameters from Core to Full Field Scale

2019 ◽  
Author(s):  
Oluwole Adesola Talabi ◽  
Jaime Eduardo Moreno ◽  
Ruppa Kumari Malhotra ◽  
Boon Keat Tham
Keyword(s):  
Field Scale ◽  
Full Field

Practical Upscaling of WAG Hysteresis Parameters from Core to Full-Field Scale Part II

2019 ◽  
Author(s):  
Oluwole A. Talabi ◽  
Jaime E. Moreno ◽  
Ruppa K. Malhotra ◽  
Yunlong Liu
Keyword(s):  
Field Scale ◽  
Full Field

Full Field Scale Hydrocarbon Gas Enhanced Oil Recovery Project in Offshore Vietnam -Response Analysis and Optimization Practice in Early Stage

2018 ◽  
Author(s):  
Yohei Kawahara ◽  
Yukiya Sako ◽  
Zhenjie Chai ◽  
Chuyen Nguyen Chu ◽  
Takahiro Murakami ◽  
...  
Keyword(s):  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Early Stage ◽  
Response Analysis ◽  
Field Scale ◽  
Full Field ◽  
Hydrocarbon Gas

An Efficient Optimization Work Flow for Field-Scale In-Situ Upgrading Developments

SPE Journal ◽  
2015 ◽  
Vol 20 (04) ◽  
pp. 701-716 ◽  
Author(s):  
Guohua Gao ◽  
Jeroen C. Vink ◽  
Faruk O. Alpak ◽  
W.. Mo
Keyword(s):  
Net Present Value ◽  
Optimization Method ◽  
Training Data ◽  
Work Flow ◽  
Surface Model ◽  
Field Scale ◽  
Full Field ◽  
Single Pattern ◽  
Gradient Based

Summary In-situ upgrading process (IUP) is an attractive technology for developing unconventional extraheavy-oil reserves. Decisions are generally made on field-scale economics evaluated with dedicated commercial tools. However, it is difficult to conduct an automated IUP optimization process because of unavailable interface between the economic evaluator and commercial simulator/optimizer, and because IUP is such a highly complex process that full-field simulations are generally not feasible. In this paper, we developed an efficient optimization work flow by addressing three technical challenges for field-scale IUP developments. The first challenge was deriving an upscaling factor modeled after analytical superposition formulation; proposing an effective method of scaling up simulation results and economic terms generated from a single-pattern IUP reservoir-simulation model to field scale; and validating this approach numerically. The second challenge was proposing a response-surface model (RSM) of field economics to analytically compute key field economical indicators, such as net present value (NPV), by use of only a few single-pattern economic terms together with the upscaling factor, and validating this approach with a commercial tool. The proposed RSM approach is more efficient, accurate, and convenient because it requires only 15–20 simulation cases as training data, compared with thousands of simulation runs required by conventional methods. The third challenge is developing a new optimization method with many attractive features: well-parallelized, highly efficient and robust, and with a much-wider spectrum of applications than gradient-based or derivative-free methods, applicable to problems without any derivative, with derivatives available for some variables, or with derivatives available for all variables. This work flow allows us to perform automated field IUP optimizations by maximizing a full-field economics target while honoring all field-level facility constraints effectively. We have applied the work flow to optimize the IUP development of a carbonate heavy-oil asset. Our results show that the approach is robust and efficient, and leads to development options with a significantly improved field-scale NPV. This work flow can also be applied to other kinds of pattern-based field developments of shale gas and oil, and thermal processes such as steamdrive or steam-assisted gravity drainage.

scholarly journals Optimization of HCG-EOR full field scale application on sand reservoir in Vietnam Rand Dong Field

2018 ◽  
Vol 83 (6) ◽  
pp. 434-441
Author(s):  
Yukiya Sako ◽  
Yohei Kawahara ◽  
Chu Chuyen Nguyen ◽  
Takahiro Murakami ◽  
Shin Kamioka ◽  
...  
Keyword(s):  
Field Scale ◽  
Full Field

Integrated Field-Scale Production and Economic Evaluation Under Subsurface Uncertainty for the Pattern-Driven Development of Unconventional Resources With Analytical Superposition

2015 ◽  
Vol 19 (01) ◽  
pp. 118-129 ◽  
Author(s):  
Guohua Gao ◽  
Jeroen C. Vink ◽  
Faruk O. Alpak
Keyword(s):  
Time Delay ◽  
Work Flow ◽  
Scale Production ◽  
Field Scale ◽  
Full Field ◽  
Unconventional Resources ◽  
Single Pattern ◽  
Pattern Development ◽  
The Impact

Summary The in-situ upgrading process (IUP) is a thermal-recovery technique that relies on a pattern-based development process, a complicated physical process that involves thermal and mass transfer in porous media, which renders full field-scale reservoir simulations impractical. Although it is feasible to quantify the impact of subsurface uncertainties on recovery for small-scale sector models with experimental design (ED), it is still a very challenging problem to quantify their impact on field-scale quantities. Straightforward upscaling to field scale does not work because such conventional superposition-based methods do not capture the effects of spatial variability in rock and fluid properties and the time delay in sequential pattern development. In this paper, we show that, under certain mild assumptions, an analytical superposition formulation can be developed that propagates the uncertainties of production forecasts and economic evaluations generated from a sector model to full field-scale quantities. One can simplify this formulation further so that the variance of a field-scale quantity is analytically expressed as the variance of the same single-pattern quantity multiplied by a (computable) scaleup factor. This makes it possible to implement a practical uncertainty quantification work flow in which single-pattern results are upscaled to accurate full field results with reliable uncertainty ranges, without the need for full field-scale simulations. We apply the proposed novel superposition and uncertainty-propagation method to a multipattern IUP development, and demonstrate that this work flow produces reliable results for field-scale production and economics as well as realistic uncertainty ranges. Moreover, these results indicate that the scaleup factor for single-pattern results can accurately capture the impact of spatial correlations of subsurface uncertainties, the size of the field-scale model, the time-delay in pattern development, and the discount rate. Uncertainty quantification of field-scale production and economics is a key factor for the successful development of unconventional resources such as extraheavy oil and oil shale with significant rewards in terms of risk management and project profitability. With minor modifications, the proposed method can also be applied to other pattern-driven processes such as the in-situ conversion process (ICP) and steam-assisted gravity drainage.

Helical Boundary Conditions To Capture Interpattern Flow in In-Situ-Upgrading-Process Pattern Simulations

SPE Journal ◽  
2016 ◽  
Vol 21 (02) ◽  
pp. 393-404 ◽  
Author(s):  
Jeroen C. Vink ◽  
Guohua Gao ◽  
Jean-Charles C. Ginestra
Keyword(s):  
Time Delay ◽  
Boundary Conditions ◽  
Production Rate ◽  
Field Scale ◽  
Field Boundary ◽  
Current Pattern ◽  
Full Field ◽  
Sector Model ◽  
Simulation Results

Summary The in-situ upgrading process (IUP) involves very complicated multiphase thermal transport and chemical reactions. Numerical simulation of IUP is computationally expensive, and direct simulation of field-scale IUP models becomes prohibitive. A practical way is to simulate a sector model under proper boundary and initial conditions and then upscale the simulation results to the full field scale with superposition techniques. Because of nonsymmetric pattern configuration and time delay of developing patterns sequentially, interpattern flow may become significant, and its impact on the simulation results cannot be neglected. Therefore, no-flow boundary conditions become inappropriate for such IUP sector models. In this paper, we proposed a new type of “helical” boundary conditions (HBCs) in which pressures and temperatures are periodic in space, except for a shift in time. The HBCs are specifically designed for a field-scale IUP development in which patterns are developed sequentially in time, along a long strip. In such a development, each pattern has exactly the same well configuration and operational schedule, except for a time delay. Because of high viscosity of heavy oil and low heat conductivity of formation rock, the impact of field boundary conditions on interpattern flow will be dampened quickly within only a few patterns, and a repetitive “pseudosteady state” of interpattern flow develops, in which the energy and mass fluxes from the previous pattern to the current pattern are the same as those from the current pattern to the next pattern, except for the delay time. By use of a 1D heat-transfer model, we analytically demonstrate that the pseudosteady state and therefore the HBCs hold for a long strip of patterns. A practical procedure to implement these HBCs in numerical simulation is developed, in which the state variables (pressure, temperature, and fluid composition) are iteratively updated in gridblocks on both edges of a sector model that is composed of two patterns. This iterative approach to impose HBCs was implemented in our in-house simulator. This approach was tested and validated by simulation results of an IUP model that is composed of 59 patterns. Our results show that the full-field boundary conditions only affect the production-rate profiles of the first and the last patterns. Production-rate profiles generated from all other patterns are almost identical except for the interpattern time delay, which also validates the pseudosteady state of interpattern flow for a more-complicated IUP model. The two-pattern sector model with the HBCs converges in three to four iterations. The production-rate profiles of oil, gas, and water generated by the sector model with HBCs are almost identical to those produced from one of those inner patterns in the 59-pattern model. With the 1D example, we also analytically demonstrate the convergence of our numerical implementation of HBCs. In terms of clock-time used, it is possible to achieve 5N time speedup through application of the HBCs, in which N is the number of patterns in a field-scale model. Therefore, the new approach is proved a key enabler for field-scale IUP pattern optimization. Provided that the interpattern-pressure communication that is induced by the pattern delay time is not too severe, we expect that one can also apply HBCs to the simulation of other field-scale thermal processes, such as the in-situ conversion process and steamfloods.

Unconstrained Voronoi Grids for Densely Spaced Complex Wells in Full-Field Reservoir Simulation

SPE Journal ◽  
2014 ◽  
Vol 19 (05) ◽  
pp. 803-815 ◽  
Author(s):  
L.S.K.. S.K. Fung ◽  
X.Y.. Y. Ding ◽  
A.H.. H. Dogru
Keyword(s):  
Finite Volume ◽  
Reservoir Simulation ◽  
Unstructured Grid ◽  
Unstructured Grids ◽  
Field Scale ◽  
Full Field ◽  
Structured Grids ◽  
Grid Simulation ◽  
Local Grid ◽  
Complex Well

Summary Accurate representation of near-well flow is an important subject matter in reservoir simulation. In today's field-scale reservoir simulation, cell-centered structured grids remain the predominant practice. Typically, well-inflow performance of the perforated cells is connected to the finite-volume solution by means of well indices that may not be well-defined when the wellbore intersects the finite-volume cells in a complex trajectory. Fine gridding is also required to resolve the flow dynamics in the near-well regions. Strong grid-orientation sensitivities can also contribute to the numerical errors and may require significant local grid refinement to alleviate. There are ongoing resesarch-and-development (R&D) efforts on applying unstructured grids to better represent the near-well flow in reservoir simulation, but their applications are mainly in single-well study or sector modeling with a few wells. Some of the reasons cited for this include (1) the lack of an effective, easy-to-use full-field complex well-gridding tool; (2) the lack of supporting unstructured workflow for full-cycle reservoir simulation; (3) the cost of unstructured-grid simulation; and (4) the availability of post-analysis and visualization tools for unstructured-grid simulation. The paper describes a novel method to automatically generate unstructured grids that conform to complex well paths in field-scale simulation. The method uses a multilevel approach to place cells optimally within the solution domain on the basis of the “regions of interests.” The wellbore geometry is honored by means of the construction of a near-well grid that is complemented with multilevel quad-tree (Fig. 1) refinements to achieve the desired resolution in grid transition zones. The method includes an algorithm to remove small cells and pinching cells on the basis of local grid quality measures and cell prioritization to honor well paths. The gridding process forms a component of a production-level reservoir-simulation workflow. The use of unstructured grid results in computational savings by placing cells where the resolution is needed. An in-house massively parallel simulator is used to run the unstructured-grid models. Simulation examples for full-field applications with hundreds of complex wells by use of both structured grids and unstructured grids will be used to compare results, accuracy, and performance of the gridding method for reservoir simulation.

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