Muskingum equation based downstream sediment flow simulation models for a river system

2016 ◽  
Vol 31 (2) ◽  
pp. 139-148 ◽  
Author(s):  
Briti Sundar Sil ◽  
Parthasarathi Choudhury
Keyword(s):  
Flow Simulation ◽  
Simulation Models ◽  
River System ◽  
Sediment Flow

scholarly journals Simulation of flood flow in a river system using artificial neural networks

2005 ◽  
Vol 9 (4) ◽  
pp. 313-321 ◽  
Author(s):  
R. R. Shrestha ◽  
S. Theobald ◽  
F. Nestmann
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Flow Simulation ◽  
Simulation Models ◽  
River System ◽  
Training Data ◽  
Data Sets ◽  
Network Training ◽  
Artificial Neural ◽  
Flood Flow

Abstract. Artificial neural networks (ANNs) provide a quick and flexible means of developing flood flow simulation models. An important criterion for the wider applicability of the ANNs is the ability to generalise the events outside the range of training data sets. With respect to flood flow simulation, the ability to extrapolate beyond the range of calibrated data sets is of crucial importance. This study explores methods for improving generalisation of the ANNs using three different flood events data sets from the Neckar River in Germany. An ANN-based model is formulated to simulate flows at certain locations in the river reach, based on the flows at upstream locations. Network training data sets consist of time series of flows from observation stations. Simulated flows from a one-dimensional hydrodynamic numerical model are integrated for network training and validation, at a river section where no measurements are available. Network structures with different activation functions are considered for improving generalisation. The training algorithm involved backpropagation with the Levenberg-Marquardt approximation. The ability of the trained networks to extrapolate is assessed using flow data beyond the range of the training data sets. The results of this study indicate that the ANN in a suitable configuration can extend forecasting capability to a certain extent beyond the range of calibrated data sets.

An Integrated Geologic and Engineering Assessment of Fracture-Flow Potential in the Ratawi Reservoir of the Wafra Field, Partitioned Neutral Zone

2008 ◽  
Vol 11 (06) ◽  
pp. 1071-1081 ◽  
Author(s):  
Amy Whitaker ◽  
C. Shah Kabir ◽  
Wayne Narr
Keyword(s):  
Transient Analysis ◽  
Water Injection ◽  
Flow Simulation ◽  
Simulation Models ◽  
Dual Porosity ◽  
Fracture Flow ◽  
Fractured Reservoir ◽  
Horizontal Drilling ◽  
Rate Transient Analysis ◽  
Production Characteristics

Summary The extent to which fractures affect fluid pathways is a vital component of understanding and modeling fluid flow in any reservoir. We examined the Wafra Ratawi grainstone for which production extending for 50 years, including recent horizontal drilling, has provided some clues about fractures, but their exact locations, intensity, and overall effect have been elusive. In this study, we find that a limited number of total fractures affect production characteristics of the Ratawi reservoir. Although fractures occur throughout the Wafra field, fracture-influenced reservoir behavior is confined to the periphery of the field where the matrix permeability is low. This work suggests that for the largest part of the field, explicit fractures are not necessary in the next-generation Earth and flow-simulation models. The geologic fracture assessment included seismic fault mapping and fracture interpretation of image logs and cores. Fracture trends are in the northeast and southwest quadrants, and fractures are mineralized toward the south and west of the field. Pressure-falloff tests on some peripheral injectors indicate partial barriers, and most of these wells lie on seismic-scale faults in the reservoir, suggesting partial sealing. A few wells show fractured-reservoir production characteristics, and rate-transient analysis on a few producers indicates localized dual-porosity behavior. Producers proximal to dual-porosity wells display single-porosity behavior, however, to attest to the notion of localized fracture response. The spatially restricted fracture-flow characteristics appear to correlate with fracture or vug zones in a low-permeability reservoir. Presence of fracture-flow behavior was tested by constructing the so-called flow-capacity index (FCI), the ratio of khwell (well test-derived value) to khmatrix (core-derived property). Data from 80 wells showed khmatrix to be consistently higher than khwell, a relationship that suggests insignificant fracture production in these wells. Introduction The Wafra field is in the Partitioned Neutral Zone (PNZ) between Kuwait and Saudi Arabia, as shown in Fig. 1. The field has been producing since the 1950s and has seen renewed drilling activity since the late 1990s, including horizontal drilling and implementation of peripheral water injection (Davis and Habib 1999). The Lower Cretaceous Ratawi formation contains the most reserves of the producing intervals at Wafra. The Ratawi oolite (a misnomer--it is a grainstone) reservoir has variable porosity (5 to 35%) and permeability that ranges from tens to hundreds of md (Longacre and Ginger 1988). The main Wafra structure is a gentle (i.e., interlimb angle >170°), doubly plunging anticline trending north-northwest to south-southeast, which culminates near its northern end. The East Wafra spur is a north-trending branch that extends from the center of the main Wafra structure. As seen in Fig. 1, relief on the Main Wafra structure exceeds that on East Wafra. The Ratawi oolite in the Wafra field has been studied at length, and various authors have reported geologic and engineering elements, leading to reservoir characterization and understanding of reservoir performance. Geologic studies are those of Waite et al. (2000) and Sibley et al. (1997). In contrast, Davis and Habib (1999) presented implementation of peripheral water injection, whereas Chawathé et al. (2006) discussed realignment of injection pattern owing to lack of pressure support in the reservoir interior. Previous studies considered the reservoir to behave like a single-porosity system. But recent image-log fracture interpretations indicate high fracture densities, suggesting that the implementation of a dual-porosity model may be necessary because the high impact of fractures during field development has been recognized in some Middle East reservoirs for more than 50 years (Daniel 1954). Static and dynamic data are required to characterize fracture reservoir behavior accurately (Narr et al. 2006). Geologic description of the fracture system, by use of cores, borehole images, seismic data, and well logs, does not in itself determine whether fractures affect reservoir behavior. While seismic and some image logs were available to locate fractures in the Wafra Ratawi reservoir, no dynamic testing with the specific objective of understanding fracture impact has occurred. So, to determine whether fractures influence oil productivity significantly, we used diagnostic analyses of production data and well tests of available injectors. The assessment of fracture effects in the Ratawi reservoir will be used to guide the next generation of geologic and flow-simulation models. Dynamic data involving pressure and rate have the potential to reveal the influence of open fractures in production performance. Unfortunately, pressure-transient testing on single wells does not always provide conclusive evidence about the presence of fractures with the characteristic dual-porosity dip on the pressure-derivative signature (Bourdet et al. 1989). That is because a correct mixture of matrix/fracture storativity must be present for the characteristic signature to appear (Serra et al. 1983). In practice, interference testing (Beliveau 1989) between wells appears to provide more-definitive clues about interwell connectivity, leading to inference about fractures. In contrast to pressure-transient testing, rate-transient analysis offers the potential to provide the same information without dedicated testing. In this field, all wells are currently on submersible pumps. Consequently, the pump-intake pressure and measured rate provided the necessary data for pressure/rate convolution or rate-transient analysis. We provide the Ratawi-reservoir case study primarily as an example of the integration of diverse geologic and engineering data to develop an assessment of fracture influence on reservoir behavior. It illustrates the use of production-data diagnostic tests to determine fracture influence in the absence of targeted fracture-analysis testing. The workflow can be applied to similar static/dynamic problems, such as fault-transmissivity determination. Secondly, this analysis illustrates the process of deciding that fractures, although present throughout the reservoir, may not lead to widespread fractured-reservoir characteristics (e.g., Allan and Sun 2003).

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.

scholarly journals 3-Dimensional modeling of 2014-Malin Landslide, Maharashtra using satellite-derived data: A quantitative approach to numerical simulation technique

2018 ◽  
Author(s):  
Shovan Lal Chattoraj ◽  
Prashant K. Champati ray ◽  
Sudhakar Pardeshi ◽  
Vikram Gupta ◽  
Yateesh Ketholia
Keyword(s):  
High Resolution ◽  
Debris Flow ◽  
Flow Simulation ◽  
Simulation Models ◽  
Quantitative Information ◽  
Simulation Technique ◽  
Maximum Height ◽  
Deccan Volcanic Province ◽  
South Indian ◽  
High Resolution Satellite Images

Abstract. Debris flows, a type of landslides, are not nowadays limited only to the periodic devastation of the geologically fragile Himalaya but also ubiquitous in weathered Deccan Volcanic Province of the cratonic south Indian peninsula. Comprehensive assessment of landslide hazard, pertinently, requires process-based modeling using simulation methods. Development of precipitation triggered debris flow simulation models of real events are still at a young stage in India, albeit, especially in tectonically less disturbed regions. A highly objective simulation technique has therefore been envisaged herein to model the debris flow run-out happened in Malin. This takes cues from a high- resolution DEM and other ancillary ground data including geotechnical and frictional parameters. The algorithm is based on Voellmy frictional (dry and turbulent frictional coefficients, μ and ξ respectively) parameters of debris flow with pre-defined release area identified on high-resolution satellite images like LISS-IV and Cartosat-1. The model provides critical quantitative information on flow 1) Velocity, 2) Height, 3) Momentum, and 4) Pressure along the entrainment path. The simulated velocity of about 16 m/s at mid-way the slide plummeted to 6.2 m/s at the base with intermittently increased and decreased values. The simulated maximum height was 3.9 m which gradually declined to 1.5 m near the bottom. The results can be beneficial in engineering intervention like the construction of check dams to digest the initial thrust of the flow and other remedial measures designed for vulnerable slope protection.

Multiscale Integration for Karst-Reservoir Flow-Simulation Models

2020 ◽  
Vol 23 (02) ◽  
pp. 518-533
Author(s):  
Manuel Gomes Correia ◽  
João Carlos von Hohendorff Filho ◽  
Denis José Schiozer
Keyword(s):  
Flow Simulation ◽  
Simulation Models ◽  
Reservoir Flow ◽  
Karst Reservoir

Integrated Characterization of Hydraulically Fractured Shale-Gas Reservoirs—Production History Matching

2015 ◽  
Vol 18 (04) ◽  
pp. 481-494 ◽  
Author(s):  
Siavash Nejadi ◽  
Juliana Y. Leung ◽  
Japan J. Trivedi ◽  
Claudio Virues
Keyword(s):  
Shale Gas ◽  
Hydraulic Fracture ◽  
History Matching ◽  
Flow Simulation ◽  
Simulation Models ◽  
Model Parameters ◽  
Fracture Parameters ◽  
Production History ◽  
Dfn Model

Summary Advancements in horizontal-well drilling and multistage hydraulic fracturing have enabled economically viable gas production from tight formations. Reservoir-simulation models play an important role in the production forecasting and field-development planning. To enhance their predictive capabilities and to capture the uncertainties in model parameters, one should calibrate stochastic reservoir models to both geologic and flow observations. In this paper, a novel approach to characterization and history matching of hydrocarbon production from a hydraulic-fractured shale is presented. This new methodology includes generating multiple discrete-fracture-network (DFN) models, upscaling the models for numerical multiphase-flow simulation, and updating the DFN-model parameters with dynamic-flow responses. First, measurements from hydraulic-fracture treatment, petrophysical interpretation, and in-situ stress data are used to estimate the initial probability distribution of hydraulic-fracture and induced-microfracture parameters, and multiple initial DFN models are generated. Next, the DFN models are upscaled into an equivalent continuum dual-porosity model with analytical techniques. The upscaled models are subjected to the flow simulation, and their production performances are compared with the actual responses. Finally, an assisted-history-matching algorithm is implemented to assess the uncertainties of the DFN-model parameters. Hydraulic-fracture parameters including half-length and transmissivity are updated, and the length, transmissivity, intensity, and spatial distribution of the induced fractures are also estimated. The proposed methodology is applied to facilitate characterization of fracture parameters of a multifractured shale-gas well in the Horn River basin. Fracture parameters and stimulated reservoir volume (SRV) derived from the updated DFN models are in agreement with estimates from microseismic interpretation and rate-transient analysis. The key advantage of this integrated assisted-history-matching approach is that uncertainties in fracture parameters are represented by the multiple equally probable DFN models and their upscaled flow-simulation models, which honor the hard data and match the dynamic production history. This work highlights the significance of uncertainties in SRV and hydraulic-fracture parameters. It also provides insight into the value of microseismic data when integrated into a rigorous production-history-matching work flow.

scholarly journals Comparison of 2D debris-flow simulation models with field events

2006 ◽  
Vol 10 (2) ◽  
pp. 241-264 ◽  
Author(s):  
D. Rickenmann ◽  
D. Laigle ◽  
B. W. McArdell ◽  
J. Hübl
Keyword(s):  
Debris Flow ◽  
Flow Simulation ◽  
Simulation Models

Coupling of 1D and 3D Flow Simulation Models for Engine Cooling

2005 ◽  
Author(s):  
Nobuyuki Yomoda ◽  
Masahiko Kubo ◽  
Norihiko Watanabe
Keyword(s):  
Flow Simulation ◽  
Simulation Models ◽  
3D Flow ◽  
Engine Cooling
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