The SPE has split the former "Management & Information" technical discipline into two new technical discplines:
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- Data Science & Engineering Analytics
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Collaborating Authors
Case Study Artificial Intelligence (AI) Assisted Numerical Reservoir Simulations in a Mature Reservoir Under Waterflood Development in the Sultanate of Oman
Shuaibi, Fakhriya Abdullah (Petroleum Development Oman) | Hadhrami, Munira Mohamed (Petroleum Development Oman) | Sheheimi, Awadh Harbouq (Petroleum Development Oman) | Agarwal, Binayak (Petroleum Development Oman) | Riyami, Qassim Mohamed (Petroleum Development Oman) | Ruqaishi, Mohammed (Petroleum Development Oman) | Habsi, Naima (Petroleum Development Oman) | Mortezazadeh, Emad (Target Oilfield Services LLC) | Mohajeri, Sina (Target Oilfield Services LLC)
Abstract PDO is transforming its field development planning by adopting digital technologies and Artificial Intelligence (AI) to improve organizational efficiency and maximize business value through swift quality decisions and an evergreen forecast. In this context, the company has approached a number of third parties to bring in solutions in this domain. In 2021 one such collaboration with 3rd party contractor to test a novel solution involving data driven AI based dynamic simulator in a mature brown fiend setting. The objective was to test the tool, the efficacy and efficiency of the process, robustness and ease of use and its utility in current setting [1]. Existing dynamic modelling workflows with conventional simulators are extremely time consuming to update and upgrade in a mature brownfield setting. These conventional and lengthy iterative process of working might leave value on the table. It is time consuming to update history match with all the extra inputs and forecast; and optimizing the development with all the input parameters within a short timeframe is always a challenge. The process employed in this approach was based on deep learning artificial neural networks (ANN) coupled with numerical simulators and along other static model inputs. The reservoir static and the flow dynamics were used as feature parameters to train the ANN, while the historical field production was used as the target parameters. The ANN training exercise identified the most contributed static and dynamic parameters to the historical production; therefore, these main parameters were given a higher weight in production forecasting and reservoir management. This AI-simulation method was expected to be faster, data driven and allow a faster testing of multiple development strategies in short time. This paper outlines the experience of an AI-assisted numerical simulation approach to unlock the potential of brown oil fields in south Oman by reducing the time spent on modelling and base case anchoring. It also enables evergreen forecasting by integrating AI techniques with numerical simulation. The AI-simulation was tried in a brown field with an existing FDP generated using conventional simulation tool where >50% of the FDP propose wells have been drilled. The outcomes from the AI-simulation result were compared with conventional simulation and with Actual field performance. Optimization was also conducted to locate the sweet spots for future drilling and WRFM opportunities. This optimized workflow has the potential to enable step change improvements in time and value for brownfield development and optimization for future developments.
ai simulation, ai simulator, algorithm, Artificial Intelligence, asia government, asset and portfolio management, assisted numerical reservoir simulation, case study artificial intelligence, Comparison, deep learning, enhanced recovery, europe government, forecast, History, machine learning, neural network, oman government, prediction, reservoir simulation, reservoir simulator, Simulation, simulator, united kingdom government, united states government, Upstream Oil & Gas, Waterflood Development, waterflooding
Country:
- Asia > Middle East > Oman (0.61)
- North America > United States > Texas > Terry County (0.54)
- North America > United States > Texas > Gaines County (0.54)
- Europe > United Kingdom > North Sea > Southern North Sea (0.54)
SPE Disciplines:
- Reservoir Description and Dynamics > Reservoir Simulation (1.00)
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Waterflooding (1.00)
- Management > Asset and Portfolio Management > Field development optimization and planning (1.00)
- Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (1.00)
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.68)
Given the important role production profiles play in key decision making and the inherent uncertainty and bias existing in the process of building them, it is essential that theQA/QC process is sufficient to test the robustness of the forecast range and ensure there is a shared understanding and buy-in of the assumptions behind it across the stakeholders involved in an asset. Getting other qualified professionals not directly involved in the development of this particular forecast to review inputs, methodology and outputs of the forecast. This is a powerful tool, particularly in mitigating the effects of human bias. Each reservoir and development is unique so there are likely to be different approaches that should all be considered. As has been mentioned throughout this document, it is essential to compare your forecast to the historical production of the field if it is already on production and appropriate analogues if it is not in production.
SPE Disciplines:
Technology:
- Information Technology > Modeling & Simulation (0.92)
- Information Technology > Communications > Collaboration (0.42)
Multicluster Fractures Propagation during Temporary Plugging Fracturing in Naturally Fractured Reservoirs Integrated with Dynamic Perforation Erosion
Zhu, Haiyan (Chengdu University of Technology and State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (Corresponding author)) | Huang, Chuhao (Chengdu University of Technology and State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation) | Tang, Xuanhe (Chengdu University of Technology and State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation) | McLennan, John David (University of Utah)
Summary Temporary plugging technology has been widely applied in multicluster fracturing for the uniform growth of multiple fractures. To investigate the propagation behavior of multiple fractures and explore a better fracturing scheme during temporary plugging fracturing, a 2D finite element method (FEM)-discrete fracture network (DFN) model is established. An improved traction-separation law is used to describe the constitutive behavior of fractures under different types of stress. The model is further integrated with the perforation pressure drop model, considering the dynamic perforation erosion effect to simulate the fracture geometry more accurately. Based on the model, the impact of the perforation erosion effect on the propagation of multicluster fractures in the naturally fractured reservoir is quantitatively evaluated first. The result showed that the effect can intensify the nonuniformity among multicluster fractures, especially under the condition of small cluster spacing. Then, the simulation for temporary plugging fracturing is carried out under different cluster spacings. Finally, the plugging time optimization in temporary plugging fracturing is explored. The model and results presented in this paper can provide new insight into the impact of the perforation erosion effect and exploration for plugging time optimization in temporary plugging fracturing.
asia government, china government, Completion Installation and Operations, complex reservoir, discharge coefficient, displacement, europe government, fracture, fracture geometry, fracture propagation, hydraulic fracturing, Modeling & Simulation, multicluster fracture, numerical simulation, perforation erosion, propagation, temporary, united states government, Upstream Oil & Gas
Country:
- North America > United States (0.69)
- Asia > China > Sichuan (0.68)
- Europe (0.67)
Oilfield Places:
- Asia > China > Sichuan > Sichuan Basin (0.99)
- Asia > China > Shandong > North China Basin > Shengli Field (0.99)
SPE Disciplines:
Summary The fast marching method (FMM)-based rapid flow simulation has been shown to accelerate simulation efficiency by orders of magnitude by transforming 3D simulation to equivalent 1D simulation using the concept of the “diffusive time of flight” (DTOF). However, the 1D transformation does not directly apply to multiwell problems. In this paper, we propose a novel DTOF-based multidomain multiresolution discretization scheme to accelerate multiwell simulation of unconventional reservoirs. Our method formulates multiwell simulation problems based on the DTOF which displays the pressure front propagation in unconventional reservoirs. The DTOF contours are used to partition the reservoir into local and shared domains. A local domain is where the flow is dominated by a single well, and the shared domain is where the fluid flow is influenced by multiple wells. The DTOF contours expand independently in local domains and interfere in the shared domain. After the partitioning, each domain is discretized using a multiresolution scheme whereby the original 3D fine mesh is preserved near the wells to account for detailed physics including gravity, and the rest of the domain is discretized into 1D mesh based on the DTOF contours to alleviate the simulation workload. The power and efficacy of our approach are demonstrated using synthetic and field-scale simulation models with different degrees of geologic and well-completion complexity. The simulation results, number of active cells, and computation time for the proposed discretization scheme are compared with the original high-fidelity 3D model for each case. The results show that the proposed method is suitable for multiwell simulation problems in unconventional reservoirs and can accelerate flow simulations by orders of magnitude with minimal loss of accuracy. The novelty of this work is the creation of DTOF-derived multiresolution discretization with local and shared domains to simplify and accelerate the calculation of subsurface flow problems, especially in unconventional reservoirs. Our workflow can be easily interfaced with commercial simulators, making it suitable for large-scale field applications.
application, Artificial Intelligence, asia government, calculation, complex reservoir, compressibility, datta-gupta, Drillstem Testing, drillstem/well testing, DTOF, eikonal equation, europe government, fast marching method, flow in porous media, Fluid Dynamics, fracture, gridblock, Modeling & Simulation, multiresolution simulation, north america government, paper, reservoir simulation, scaling method, seismic surveying, shale gas, Simulation, transmissibility, unconventional reservoir, unconventional resource technology conference, united states government, Upstream Oil & Gas
Country:
- North America > United States > Texas (1.00)
- Europe (0.93)
- Asia (0.93)
Industry:
- Energy > Oil & Gas > Upstream (1.00)
- Government > Regional Government > North America Government > United States Government (0.46)
Oilfield Places:
SPE Disciplines:
- Reservoir Description and Dynamics > Reservoir Simulation > Scaling methods (1.00)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Flow in porous media (1.00)
- Reservoir Description and Dynamics > Formation Evaluation & Management > Drillstem/well testing (0.95)
- Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale gas (0.93)
Technology:
Summary The distribution of low-salinity benefit for an ensemble of models is required to evaluate low-salinity enhanced oil recovery (OREC) projects. To enable this, low-salinity pseudorelative permeability curves are required to estimate the benefit of low-salinity waterflooding at the field level. We present how the low-salinity benefit can be propagated through an ensemble of full-field models in which each simulation case could have a set of distinctive high-salinity pseudos. A 0.5-ft vertical resolution sector and its 10-ft upscaled counterpart are used. Relative permeability curves and the low-salinity benefit from corefloods are used in the high-resolution sector to create profiles. Pseudohigh- and low-salinity curves are generated for the upscaled sector by history matching high-salinity and incremental low-salinity profiles. Low-salinity benefit is typically measured from corefloods and the same benefit is often assumed at the field scale. Our results show that generating low-salinity curves for high-salinity pseudos using low-salinity benefit from corefloods slightly underestimates the true low-salinity benefit at field scale estimated from high-resolution models. This conclusion is consistent for two extreme relative permeability scenarios tested (i.e., a high-total-mobility unfavorable fractional flow and low-total-mobility favorable fractional flow). Including capillary pressure in high-resolution models was crucial. We would have come to another conclusion if we had not used capillary pressure in fine-grid simulation as approximately one-third of the benefit of low-salinity waterflooding was attributable to more favorable capillary pressure under low-salinity injection. We demonstrate how a set of high-salinity relative permeability data obtained from corefloods, which encompasses a range for fractional flow and total mobility, can be included in ensemble modeling appropriately and how low-salinity benefit could be estimated for such an ensemble. It is adequate to generate low-salinity curves for bounding high-salinity sets of curves. The bounding low-salinity curves can then be used to estimate low-salinity curve for any interpolated high-salinity curve. This workflow significantly simplifies the process of generating the distribution of low-salinity benefit corresponding to an ensemble of models which may be calibrated to limited history.
asia government, Conference, coreflood, enhanced recovery, ensemble, europe government, flooding, flow in porous media, Fluid Dynamics, high-salinity pseudo, injection, Jerauld, Kuwait government, mobility, Modeling & Simulation, orec, paper, permeability, pseudo, pseudocurve, reservoir simulation, resolution, scale, spe annual technical conference, SPE Journal, uae government, united kingdom government, united states government, Upstream Oil & Gas
Country:
- Europe > United Kingdom (0.67)
- North America > United States > Texas (0.46)
- Asia > Middle East > UAE (0.29)
- Asia > Middle East > Kuwait (0.28)
Oilfield Places:
- North America > United States > Alaska > North Slope Basin > Duck Island Field > Endicott Field > Kekiktuk Formation (0.99)
- Europe > United Kingdom > North Sea > Northern North Sea > East Shetland Basin > Block 211/7a > Magnus Field > Kimmeridge Formation > Magnus Formation (0.99)
- Europe > United Kingdom > North Sea > Northern North Sea > East Shetland Basin > Block 211/7a > Magnus Field > Kimmeridge Formation > Lower Kimmeridge Clay Formation (0.99)
- (15 more...)
SPE Disciplines:
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