A Practical Approach to Incorporate Data-Driven 4D Seismic Inversion into Flow Simulation History Matching

2017 ◽  
Author(s):  
Alvaro Rey ◽  
Jorge L. Landa
Keyword(s):  
History Matching ◽  
Flow Simulation ◽  
Seismic Inversion ◽  
Practical Approach ◽  
Data Driven ◽  
4D Seismic

Tupi Nodes pilot: A successful 4D seismic case for Brazilian presalt reservoirs

2021 ◽  
Vol 40 (12) ◽  
pp. 886-896
Author(s):  
Nathalia Martinho Cruz ◽  
José Marcelo Cruz ◽  
Leonardo Márcio Teixeira ◽  
Mônica Muzzette da Costa ◽  
Laryssa Beatriz de Oliveira ◽  
...  
Keyword(s):  
Oil Recovery ◽  
History Matching ◽  
Oil And Gas ◽  
Feasibility Studies ◽  
Oil And Gas Industry ◽  
Time Lapse ◽  
Seismic Inversion ◽  
Carbonate Reservoirs ◽  
Ocean Bottom ◽  
4D Seismic

The oil and gas industry has established 4D seismic as a key tool to maximize oil recovery and operational safety in siliciclastic and low- to medium-stiffness carbonate reservoirs. However, for the stiffer carbonate reservoirs of the Brazilian presalt, the value of 4D seismic is still under debate. Tupi Field has been the stage of a pioneering 4D seismic project to field test the time-lapse technique's ability in monitoring production and water-alternating-gas (WAG) injection in the Brazilian presalt. Ocean-bottom node (OBN) technology was applied for the first time in the ultra-deep waters of Santos Basin, leading to the Tupi Nodes pilot project. We started with feasibility studies to forecast the presalt carbonate time-lapse responses. The minerals that constitute these carbonate rocks have an incompressibility modulus that is generally twice as large as those of siliciclastic rocks. This translates into discrete 4D signals that require enhanced seismic acquisition and processing techniques to be correctly detected and mapped. Consequently, two OBN seismic acquisitions were carried out. Time-lapse processing included the application of top-of-the-line processing tools, such as interbed multiple attenuation. The resulting 4D amplitude images demonstrate good signal-to-noise ratio, supporting both static and dynamic interpretations that are compatible with injection and production histories. To unlock the potential of 4D quantitative interpretation and the future employment of 4D-assisted history-matching workflows, we conducted a 4D seismic inversion test. Acoustic impedance variations of about 1.5% are reliably distinguishable beyond the immediate vicinity of the wells. These 4D OBN seismic surveys and interpretations will assist in identifying oil-bypassed targets for infill wells and calibrating WAG cycles, increasing oil recovery. We anticipate that studies of the entire Brazilian presalt section will greatly benefit from the results and conclusions already reached for Tupi Field.

Using 4D Seismic Surveys and History Matching to Estimate Critical and Maximum Gas Saturation

2014 ◽  
Author(s):  
Dennis Chinedu Obidegwu ◽  
Romain Louis Chassagne ◽  
Colin Macbeth
Keyword(s):  
History Matching ◽  
Seismic Surveys ◽  
Gas Saturation ◽  
4D Seismic

Hybrid Fluid Flow Simulation Combining Full Physics Simulation and Artificial Intelligence

2021 ◽  
Author(s):  
Mokhles Mezghani ◽  
Mustafa AlIbrahim ◽  
Majdi Baddourah
Keyword(s):  
Artificial Intelligence ◽  
Reservoir Simulation ◽  
History Matching ◽  
Hybrid Approach ◽  
Flow Simulation ◽  
Latin Hypercube Sampling ◽  
Simulation Models ◽  
Fine Scale ◽  
Simulation Results ◽  
Optimization Loop

Abstract Reservoir simulation is a key tool for predicting the dynamic behavior of the reservoir and optimizing its development. Fine scale CPU demanding simulation grids are necessary to improve the accuracy of the simulation results. We propose a hybrid modeling approach to minimize the weight of the full physics model by dynamically building and updating an artificial intelligence (AI) based model. The AI model can be used to quickly mimic the full physics (FP) model. The methodology that we propose consists of starting with running the FP model, an associated AI model is systematically updated using the newly performed FP runs. Once the mismatch between the two models is below a predefined cutoff the FP model is switch off and only the AI model is used. The FP model is switched on at the end of the exercise either to confirm the AI model decision and stop the study or to reject this decision (high mismatch between FP and AI model) and upgrade the AI model. The proposed workflow was applied to a synthetic reservoir model, where the objective is to match the average reservoir pressure. For this study, to better account for reservoir heterogeneity, fine scale simulation grid (approximately 50 million cells) is necessary to improve the accuracy of the reservoir simulation results. Reservoir simulation using FP model and 1024 CPUs requires approximately 14 hours. During this history matching exercise, six parameters have been selected to be part of the optimization loop. Therefore, a Latin Hypercube Sampling (LHS) using seven FP runs is used to initiate the hybrid approach and build the first AI model. During history matching, only the AI model is used. At the convergence of the optimization loop, a final FP model run is performed either to confirm the convergence for the FP model or to re iterate the same approach starting from the LHS around the converged solution. The following AI model will be updated using all the FP simulations done in the study. This approach allows the achievement of the history matching with very acceptable quality match, however with much less computational resources and CPU time. CPU intensive, multimillion-cell simulation models are commonly utilized in reservoir development. Completing a reservoir study in acceptable timeframe is a real challenge for such a situation. The development of new concepts/techniques is a real need to successfully complete a reservoir study. The hybrid approach that we are proposing is showing very promising results to handle such a challenge.

Application of 4D Seismic Response as a Screening Tool in Assisted History Matching

2011 ◽  
Author(s):  
Olatunji Bakare ◽  
Jonathan Umurhohwo ◽  
John Ikomi ◽  
Arinze Okonkwo ◽  
Tope Fehintola ◽  
...  
Keyword(s):  
Seismic Response ◽  
History Matching ◽  
Screening Tool ◽  
Assisted History Matching ◽  
4D Seismic

A method for performing history matching of reservoir flow models using 4D seismic data

2003 ◽  
Vol 9 (1) ◽  
pp. 83-90 ◽  
Author(s):  
M. Lygren ◽  
K. Fagervik ◽  
T.S. Valen ◽  
A. Hetlelid ◽  
G. Berge ◽  
...  
Keyword(s):  
Seismic Data ◽  
History Matching ◽  
Flow Models ◽  
Reservoir Flow ◽  
4D Seismic
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