Estimation of Future Production Performance Based on Multi-objective History Matching in a Waterflooding Project

2010 ◽  
Author(s):  
Yumi Han ◽  
Changhyup Park ◽  
Joo Myung Kang
Keyword(s):  
History Matching ◽  
Production Performance ◽  
Multi Objective ◽  
Future Production

scholarly journals Efficient Dimensionality Reduction Methods in Reservoir History Matching

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3137
Author(s):  
Amine Tadjer ◽  
Reider B. Bratvold ◽  
Remus G. Hanea
Keyword(s):  
Data Assimilation ◽  
Dimensionality Reduction ◽  
Gaussian Process ◽  
Latent Variable ◽  
History Matching ◽  
Production Performance ◽  
Latent Variable Model ◽  
Variable Model ◽  
Multiple Data ◽  
Ensemble Smoother

Production forecasting is the basis for decision making in the oil and gas industry, and can be quite challenging, especially in terms of complex geological modeling of the subsurface. To help solve this problem, assisted history matching built on ensemble-based analysis such as the ensemble smoother and ensemble Kalman filter is useful in estimating models that preserve geological realism and have predictive capabilities. These methods tend, however, to be computationally demanding, as they require a large ensemble size for stable convergence. In this paper, we propose a novel method of uncertainty quantification and reservoir model calibration with much-reduced computation time. This approach is based on a sequential combination of nonlinear dimensionality reduction techniques: t-distributed stochastic neighbor embedding or the Gaussian process latent variable model and clustering K-means, along with the data assimilation method ensemble smoother with multiple data assimilation. The cluster analysis with t-distributed stochastic neighbor embedding and Gaussian process latent variable model is used to reduce the number of initial geostatistical realizations and select a set of optimal reservoir models that have similar production performance to the reference model. We then apply ensemble smoother with multiple data assimilation for providing reliable assimilation results. Experimental results based on the Brugge field case data verify the efficiency of the proposed approach.

Gravity Drainage System: Investigation and Field Development Using Geological Modelling and Reservoir Simulation

2021 ◽  
Author(s):  
Obinna Somadina Ezeaneche ◽  
Robinson Osita Madu ◽  
Ishioma Bridget Oshilike ◽  
Orrelo Jerry Athoja ◽  
Mike Obi Onyekonwu
Keyword(s):  
Reservoir Simulation ◽  
Structural Control ◽  
History Matching ◽  
Drainage System ◽  
Production Performance ◽  
Gravity Drainage ◽  
Base Case ◽  
Proper Understanding ◽  
Field Development ◽  
Reservoir Performance

Abstract Proper understanding of reservoir producing mechanism forms a backbone for optimal fluid recovery in any reservoir. Such an understanding is usually fostered by a detailed petrophysical evaluation, structural interpretation, geological description and modelling as well as production performance assessment prior to history matching and reservoir simulation. In this study, gravity drainage mechanism was identified as the primary force for production in reservoir X located in Niger Delta province and this required proper model calibration using variation of vertical anisotropic ratio based on identified facies as against a single value method which does not capture heterogeneity properly. Using structural maps generated from interpretation of seismic data, and other petrophysical parameters from available well logs and core data such as porosity, permeability and facies description based on environment of deposition, a geological model capturing the structural dips, facies distribution and well locations was built. Dynamic modeling was conducted on the base case model and also on the low and high case conceptual models to capture different structural dips of the reservoir. The result from history matching of the base case model reveals that variation of vertical anisotropic ratio (i.e. kv/kh) based on identified facies across the system is more effective in capturing heterogeneity than using a deterministic value that is more popular. In addition, gas segregated fastest in the high case model with the steepest dip compared to the base and low case models. An improved dynamic model saturation match was achieved in line with the geological description and the observed reservoir performance. Quick wins scenarios were identified and this led to an additional reserve yield of over 1MMSTB. Therefore, structural control, facies type, reservoir thickness and nature of oil volatility are key forces driving the gravity drainage mechanism.

scholarly journals Development of a robust multi-objective history matching for reliable well-based production forecasts

2016 ◽  
Vol 34 (6) ◽  
pp. 795-809 ◽  
Author(s):  
Baehyun Min ◽  
Joe M Kang ◽  
Hoyoung Lee ◽  
Suryeom Jo ◽  
Changhyup Park ◽  
...  
Keyword(s):  
History Matching ◽  
Multi Objective

Application Investigation of Light Proppant in Hydraulic Fracturing of Marcellus Shale

2021 ◽  
Author(s):  
Aymen Alhemdi ◽  
Ming Gu
Keyword(s):  
History Matching ◽  
Marcellus Shale ◽  
In Situ Stress ◽  
Production Performance ◽  
Well Performance ◽  
Fracture Permeability ◽  
Fracture Conductivity ◽  
Stimulated Reservoir Volume ◽  
Conductivity Distribution ◽  
Cumulative Production

Abstract Slickwater-sand fracturing design is widely employed in Marcellus shale. The slickwater- sand creates long skinny fractures and maximizes the stimulated reservoir volume (SRV). However, due to the fast settling of sand in the water, lots of upper and deeper areas are not sufficiently propped. Reducing sand size can lead to insufficient fracture conductivity. This study proposes to use three candidate ultra-lightweight proppants ULWPs to enhance the fractured well performance in unconventional reservoirs. In step 1, the current sand pumping design is input into an in-house P3D fracture propagation simulator to estimate the fracture geometry and proppant concentrations. Next, the distribution of proppant concentration converts to conductivity and then to fracture permeability. In the third step, the fracture permeability from the second step is input into a reservoir simulator to predict the cumulative production for history matching and calibration. In step 4, the three ULWPs are used to replace the sand in the frac simulator to get new frac geometry and conductivity distribution and then import them in reservoir model for production evaluation. Before this study, the three ULWPs have already been tested in the lab to obtain their long-term conductivities under in-situ stress conditions. The conductivity distribution and production performance are analyzed and investigated. The induced fracture size and location of the produced layer for the current target well play a fundamental effect on ultra-light proppant productivity. The average conductivity of ULWPs with mesh 40/70 is larger and symmetric along the fracture except for a few places. However, ULWPs with mesh 100 generates low average conductivity and create a peak conductivity in limited areas. The ULW-3 tends to have less cumulative production compared with the other ULWPs. For this Marcellus Shale study, the advantages of ultra-lightweight proppant are restricted and reduced because the upward fracture height growth is enormous. And with the presence of the hydrocarbon layer is at the bottom of the fracture, making a large proportion of ULWPs occupies areas that are not productive places. The current study provides a guidance for operators in Marcellus Shale to determine (1) If the ULWP can benefit the current shale well treated by sand, (2) what type of ULWP should be used, and (3) given a certain type of ULWP, what is the optimum pumping schedule and staging/perforating design to maximize the well productivity. The similar workflow can be expanded to evaluate the economic potential of different ULWPs in any other unconventional field.

Numerical Comparison Between ES-MDA and Gradient-Based Optimization for History Matching of Reduced Reservoir Models

2021 ◽  
Author(s):  
M. A. Borregales Reverón ◽  
H. H. Holm ◽  
O. Møyner ◽  
S. Krogstad ◽  
K.-A. Lie
Keyword(s):  
History Matching ◽  
Automatic Differentiation ◽  
Computational Cost ◽  
Numerical Comparison ◽  
Petroleum Reservoir ◽  
History Match ◽  
Reservoir Models ◽  
Multiple Data ◽  
Future Production ◽  
Gradient Based

Abstract The Ensemble Smoother with Multiple Data Assimilation (ES-MDA) method has been popular for petroleum reservoir history matching. However, the increasing inclusion of automatic differentiation in reservoir models opens the possibility to history-match models using gradient-based optimization. Here, we discuss, study, and compare ES-MDA and a gradient-based optimization for history-matching waterflooding models. We apply these two methods to history match reduced GPSNet-type models. To study the methods, we use an implementation of ES-MDA and a gradient-based optimization in the open-source MATLAB Reservoir Simulation Toolbox (MRST), and compare the methods in terms of history-matching quality and computational efficiency. We show complementary advantages of both ES-MDA and gradient-based optimization. ES-MDA is suitable when an exact gradient is not available and provides a satisfactory forecast of future production that often envelops the reference history data. On the other hand, gradient-based optimization is efficient if the exact gradient is available, as it then requires a low number of model evaluations. If the exact gradient is not available, using an approximate gradient or ES-MDA are good alternatives and give equivalent results in terms of computational cost and quality predictions.

A Simplified and Efficient Method for Water Flooding Production Index Calculations in Low Permeable Fractured Reservoir

2019 ◽  
Vol 141 (11) ◽  
Author(s):  
Shun Liu ◽  
Liming Zhang ◽  
Kai Zhang ◽  
Jianren Zhou ◽  
Heng He ◽  
...  
Keyword(s):  
Fractured Reservoirs ◽  
Water Injection ◽  
Cross Flow ◽  
Production Performance ◽  
Water Flooding ◽  
Simplified Model ◽  
Single Fracture ◽  
Fractured Reservoir ◽  
Production Index ◽  
Future Production

Presently, predicting the production performance of fractured reservoirs is often challenging because of the following two factors: one factor such as complicatedly connected and random distribution nature of the fractures and the other factor includes the limitations of the understanding of reservoir geology, deficient fracture-related research, and defective simulators. To overcome the difficulties of simulating and predicting fractured reservoir under complex circumstances of cross flow, a simplified model, which assumes cross flow only exists in the oil phase segment, is constructed. In the model, the pressure distribution of a single fracture can be described by solving an analytical mathematical model. In addition, due to research and field experience which indicate that cross flow also exists in the mixed-phase segment after water injection, the simplified model is modified to consider cross flow in the whole phase. The model constructed here is applicable for fractured reservoirs especially for a low-permeability fracture reservoir, and it moderately predicts future production index. By using iterative methods, the solution to the model can be feasibly obtained and related production performance index formulas can be derived explicitly. A case study was performed to test the model, and the results prove that it is good.

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