A New Simulation Layer Optimization and Permeability Upscaling Method for Preserving Critical Reservoir Heterogeneity

2021 ◽  
Author(s):  
Dachang Li ◽  
Corneliu-Liviu Ionescu ◽  
Baurzhan Muftakhidinov ◽  
Byron Haynes ◽  
Bakyt Yergaliyeva
Keyword(s):  
History Matching ◽  
Cost Effective ◽  
Coarse Grid ◽  
Oil Field ◽  
Reservoir Properties ◽  
The Caspian Sea ◽  
Fine Grid ◽  
Grid Model ◽  
Compositional Model ◽  
Permeability Upscaling

Abstract Running a fine grid model with 107 - 109 of cells is possible using a supercomputer with 103 - 106 of CPUs but may not be always cost-effective. The most cost-effective way is to use a coarse grid model that is much smaller but with static/dynamic profiles very close to the fine grid model. This paper proposes a new layer optimization and upscaling method with the aim for creating a consistent coarse grid model. Unlike the industry's existing layer optimization and upscaling methods, the proposed method performs layer optimization and upscaling fully integrated with the Lorenz coefficient and curves (LCC). Coarse grid layers and their permeabilities are created by minimizing the difference between fine and coarse grid LCCs. The process consists of static and dynamic optimizations. The former is measured by LCC while the latter by pressure, GOR, and water-cut. A new LCC-based permeability upscaling method is developed to preserve the fine grid multiphase flow behaviors. A satisfactory coarse grid model is achieved when both static and dynamic criteria are met. The proposed method has been successfully applied to a giant carbonate oil field in the Caspian Sea that consists of a matrix dominated platform and a fracture/karst dominated rim. Due to the field's complex geology and high H2S content (15%), a dual porosity, dual permeability compositional model has been created to model compositional sour crude flow within and between the matrix and fracture/karst features. The reservoir drive mechanisms are fluid expansion, miscible gas injection and aquifer drive. The reservoir is undersaturated and has an abnormally high initial reservoir pressure. The fine-grid static model contains 104 million cells (370×225×625×2) and the optimized upscaled coarse-grid dynamic model has 8.3 million cells (370×225×50×2). The upscaled model can be run efficiently on the company's existing HPC infrastructure with a maximum of 64 CPUs. Excellent matches of the Lorenz coefficient maps for reservoir total/zones and Lorenz curves at all wells between the fine and coarse grid models have been achieved. Matches on the dynamic variables, e.g., pressure, gas breakthrough time, and GOR growth, in all producers are within the defined acceptable tolerances. The high quality of the static and dynamic matches between the coarse- and fine-grid models confirms that the reservoir properties of the coarse-grid model is very close to the fine-grid model and can be used a base model for history matching and uncertainty analysis.

A Nested-Grid Hydrodynamic/Pollutant Transport Model for Nearshore Areas in Hamilton Harbour

1995 ◽  
Vol 30 (2) ◽  
pp. 205-230 ◽  
Author(s):  
Ioannis K. Tsanis ◽  
Jian Wu
Keyword(s):  
Transport Model ◽  
Pollutant Transport ◽  
Coarse Grid ◽  
Fine Grid ◽  
Flushing Time ◽  
Grid Model ◽  
Hamilton Harbour ◽  
Nested Grid ◽  
Water Elevations ◽  
The Impact

Abstract A nested-grid depth-averaged circulation model was developed and applied to three nearshore areas in Hamilton Harbour: the western basin, LaSalle Park waterfront and the northeastern shoreline. The grid sizes used were 100 m for the whole harbour, and 25 m for the three nearshore areas. General features of current circulation and horizontal mixing times under various wind directions and speeds were obtained for the whole harbour using the coarse-grid model. The fine-grid model (water elevations and current information on the open boundaries were obtained from the whole harbour model) then provided current patterns which were used to drive the pollutant transport model. Simulation results reveal that the current in the fine-grid model is close to the current from the coarse-grid model, while more detailed current structures are explored. The water elevations from the fine-grid model agree well with the elevations from the coarse-grid one. The impact of artificial islands was examined by studying changes in current patterns, pollutant peaks, exposure and flushing time in different locations of concern. The design proposed provides: (i) minimum change in the existing current patterns; (ii) avoidance of pollutant hot spots; and (iii) minimum changes in the flushing time of pollutants.

Data Assimilation Using the Constrained Ensemble Kalman Filter

SPE Journal ◽  
2010 ◽  
Vol 16 (02) ◽  
pp. 331-342 ◽  
Author(s):  
Hemant A. Phale ◽  
Dean S. Oliver
Keyword(s):  
Kalman Filter ◽  
Data Assimilation ◽  
Ensemble Kalman Filter ◽  
History Matching ◽  
Model Parameters ◽  
State Variables ◽  
Reservoir Properties ◽  
Compositional Model ◽  
Highly Nonlinear ◽  
Nonnegativity Constraints

Summary When the ensemble Kalman filter (EnKF) is used for history matching, the resulting updates to reservoir properties sometimes exceed physical bounds, especially when the problem is highly nonlinear. Problems of this type are often encountered during history matching compositional models using the EnKF. In this paper, we illustrate the problem using an example in which the updated molar density of CO2 in some regions is observed to take negative values while molar densities of the remaining components are increased. Standard truncation schemes avoid negative values of molar densities but do not address the problem of increased molar densities of other components. The results can include a spurious increase in reservoir pressure with a subsequent inability to maintain injection. In this paper, we present a method for constrained EnKF (CEnKF), which takes into account the physical constraints on the plausible values of state variables during data assimilation. In the proposed method, inequality constraints are converted to a small number of equality constraints, which are used as virtual observations for calibrating the model parameters within plausible ranges. The CEnKF method is tested on a 2D compositional model and on a highly heterogeneous three-phase-flow reservoir model. The effect of the constraints on mass conservation is illustrated using a 1D Buckley-Leverett flow example. Results show that the CEnKF technique is able to enforce the nonnegativity constraints on molar densities and the bound constraints on saturations (all phase saturations must be between 0 and 1) and achieve a better estimation of reservoir properties than is obtained using only truncation with the EnKF.

A Case Study in Scaleup for Multicontact Miscible Hydrocarbon Gas Injection

1998 ◽  
Vol 1 (06) ◽  
pp. 575-582 ◽  
Author(s):  
G.R. Jerauld
Keyword(s):  
Relative Permeability ◽  
Oil Recovery ◽  
History Matching ◽  
Fine Grid ◽  
Full Field ◽  
Compositional Model ◽  
Three Phase ◽  
Solvent Retention ◽  
Hydrocarbon Gas ◽  
Relative Permeability Curves

Summary We describe the strategy and results of scaleup done to simulate a multicontact miscible hydrocarbon water alternating gas (WAG) injection process. To adequately model both oil recovery and solvent retention in WAG, one must model three-phase flow including gas trapping. Scaleup of the multicontact miscible gas process is particularly difficult because of the very fine-scale structure of the gas fingers and the miscible front. The case studied is a heterogeneous mixed wet reservoir with a transition zone down to an underlying aquifer. The objective was to develop pseudo relative permeability curves and other parameters that are suitable for running in a full-field limited compositional model with three hydrocarbon components. Both history-matching and systematic approaches were used to generate pseudo relative permeability curves that reproduced results of high-resolution, fully compositional (FC) reference simulations. Dynamic pseudoization techniques were used to derive first guesses at pseudos, but required further calibration to reproduce reference simulations successfully. In matching incremental miscible gas/oil recovery timing and solvent retention, varying three phase water relative permeability was much more effective than varying the mixing parameter. The predictive capability of pseudos was tested for changes with respect to slug size, WAG ratio, and solvent enrichment. Pseudos derived for one pattern or cross section were tested in other patterns or cross sections. Pseudos worked well with respect to changes in WAG ratio, fairly well with respect to changes in solvent enrichment, and moderately well for changes in slug size. They were less robust with respect to changes in description. Introduction Estimation of the incremental recovery and solvent utilization in a multicontact miscible hydrocarbon gas process is challenging. On one hand, important features of the process occur over small-length scales and cannot be estimated readily without very fine-grid, FC simulation. The condensing/vaporizing drive entails the concentration of enriching components into a narrow miscible front that is smeared by coarse areal gridding. High vertical grid refinement is needed to capture thin gas fingers that form within layers of high permeability. SPE 53006 was revised for publication from paper SPE 39626, first presented at the 1998 SPE/DOE Improved Oil Recovery Symposium, Tulsa, Oklahoma, 19-22 April.

scholarly journals CO$$_{2}$$ Convection in Hydrocarbon Under Flowing Conditions

2021 ◽  
Author(s):  
Trine S. Mykkeltvedt ◽  
Sarah E. Gasda ◽  
Tor Harald Sandve
Keyword(s):  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Flow Behavior ◽  
Cost Effective ◽  
Fine Grid ◽  
Cost Effective Method ◽  
Gravity Effects ◽  
Petroleum Resources ◽  
Nearby Point ◽  
Diffusive Processes

AbstractCarbon-neutral oil production is one way to improve the sustainability of petroleum resources. The emissions from produced hydrocarbons can be offset by injecting capture CO$$_{2}$$ 2 from a nearby point source into a saline aquifer for storage or a producing oil reservoir. The latter is referred to as enhanced oil recovery (EOR) and would enhance the economic viability of CO$$_{2}$$ 2 sequestration. The injected CO$$_{2}$$ 2 will interact with the oil and cause it to flow more freely within the reservoir. Consequently, the overall recovery of oil from the reservoir will increase. This enhanced oil recovery (EOR) technique is perceived as the most cost-effective method for disposing captured CO$$_{2}$$ 2 emissions and has been performed for many decades with the focus on oil recovery. The interaction between existing oil and injected CO$$_{2}$$ 2 needs to be fully understood to effectively manage CO$$_{2}$$ 2 migration and storage efficiency. When CO$$_{2}$$ 2 and oil mix in a fully miscible setting, the density can change non-linearly and cause density instabilities. These instabilities involve complex convective-diffusive processes, which are hard to model and simulate. The interactions occur at the sub-centimeter scale, and it is important to understand its implications for the field scale migration of CO$$_{2}$$ 2 and oil. In this work, we simulate gravity effects, namely gravity override and convective mixing, during miscible displacement of CO$$_{2}$$ 2 and oil. The flow behavior due to the competition between viscous and gravity effects is complex, and can only be accurately simulated with a very fine grid. We demonstrate that convection occurs rapidly, and has a strong effect on breakthrough of CO$$_{2}$$ 2 at the outlet. This work for the first time quantifies these effects for a simple system under realistic conditions.

scholarly journals Injection-production optimization of carbonate reservoir based on an inter-well connectivity model

2021 ◽  
pp. 014459872199465
Author(s):  
Yuhui Zhou ◽  
Sheng Lei ◽  
Xuebiao Du ◽  
Shichang Ju ◽  
Wei Li
Keyword(s):  
History Matching ◽  
Water Injection ◽  
Field Application ◽  
Carbonate Reservoir ◽  
Production Optimization ◽  
Oil Field ◽  
Carbonate Reservoirs ◽  
Utilization Rate ◽  
Production Volume ◽  
Connectivity Model

Carbonate reservoirs are highly heterogeneous. During waterflooding stage, the channeling phenomenon of displacing fluid in high-permeability layers easily leads to early water breakthrough and high water-cut with low recovery rate. To quantitatively characterize the inter-well connectivity parameters (including conductivity and connected volume), we developed an inter-well connectivity model based on the principle of inter-well connectivity and the geological data and development performance of carbonate reservoirs. Thus, the planar water injection allocation factors and water injection utilization rate of different layers can be obtained. In addition, when the proposed model is integrated with automatic history matching method and production optimization algorithm, the real-time oil and water production can be optimized and predicted. Field application demonstrates that adjusting injection parameters based on the model outputs results in a 1.5% increase in annual oil production, which offers significant guidance for the efficient development of similar oil reservoirs. In this study, the connectivity method was applied to multi-layer real reservoirs for the first time, and the injection and production volume of injection-production wells were repeatedly updated based on multiple iterations of water injection efficiency. The correctness of the method was verified by conceptual calculations and then applied to real reservoirs. So that the oil field can increase production in a short time, and has good application value.

Nanotechnology Helps Decrease Pressure, Increase Injection in Offshore China Oil Field

2021 ◽  
Vol 73 (09) ◽  
pp. 58-59
Author(s):  
Chris Carpenter
Keyword(s):  
Water Injection ◽  
Injection Pressure ◽  
Gas Production ◽  
Oil Field ◽  
Water Flooding ◽  
Injection System ◽  
Bohai Bay ◽  
Reservoir Properties ◽  
Positive Effects ◽  
Offshore Technology

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 30407, “Case Study of Nanopolysilicon Materials’ Depressurization and Injection-Increasing Technology in Offshore Bohai Bay Oil Field KL21-1,” by Qing Feng, Nan Xiao Li, and Jun Zi Huang, China Oilfield Services, et al., prepared for the 2020 Offshore Technology Conference Asia, originally scheduled to be held in Kuala Lumpur, 2–6 November. The paper has not been peer reviewed. Copyright 2020 Offshore Technology Conference. Reproduced by permission. Nanotechnology offers creative approaches to solve problems of oil and gas production that also provide potential for pressure-decreasing application in oil fields. However, at the time of writing, successful pressure-decreasing nanotechnology has rarely been reported. The complete paper reports nanopolysilicon as a new depressurization and injection-increasing agent. The stability of nanopolysilicon was studied in the presence of various ions, including sodium (Na+), calcium (Ca2+), and magnesium (Mg2+). The study found that the addition of nanomaterials can improve porosity and permeability of porous media. Introduction More than 600 water-injection wells exist in Bohai Bay, China. Offshore Field KL21-1, developed by water-flooding, is confronted with the following challenges: - Rapid increase and reduction of water-injection pressure - Weak water-injection capacity of reservoir - Decline of oil production - Poor reservoir properties - Serious hydration and expansion effects of clay minerals To overcome injection difficulties in offshore fields, conventional acidizing measures usually are taken. But, after multiple cycles of acidification, the amount of soluble substances in the rock gradually decreases and injection performance is shortened. Through injection-performance experiments, it can be determined that the biological nanopolysilicon colloid has positive effects on pressure reduction and injection increase. Fluid-seepage-resistance decreases, the injection rate increases by 40%, and injection pressure decreases by 10%. Features of Biological Nanopolysilicon Systems The biological nanopolysilicon-injection system was composed of a bioemulsifier (CDL32), a biological dispersant (DS2), and a nanopolysilicon hydrophobic system (NP12). The bacterial strain of CDL32 was used to obtain the culture colloid of biological emulsifier at 37°C for 5 days. DS2 was made from biological emulsifier CDL32 and some industrial raw materials described in Table 1 of the complete paper. Nanopolysilicon hydrophobic system NP12 was composed of silicon dioxide particles. The hydrophobic nanopolysilicons selected in this project featured particle sizes of less than 100 nm. In the original samples, a floc of nanopolysilicon was fluffy and uniform. But, when wet, nanopolysilicon will self-aggregate and its particle size increases greatly. At the same time, nanopolysilicon features significant agglomeration in water. Because of its high interface energy, nanopolysilicon is easily agglomerated, as shown in Fig. 1.

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