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Development of a natural gas field by depletion drive is characterized by a decrease of average formation pressure, bottom hole and wellhead pressures of production wells over time. As a rule, during the initial field development period available formation pressure is sufficient for gas transportation from wellheads to a treatment facility and then to a tie-in to the trunk gas pipeline without using the compressor equipment. However, the formation pressure is decreasing gradually during the whole field life and this in turn leads to a decrease in the entire system "Reservoir - Well - Infield Gas Collection Networks - Gas Treatment Plant". There comes a point of time when the pressure of gas at the gas treatment plant (GTP) inlet becomes insufficient for its treatment and further supply into the trunk gas pipeline under the required pressure and flow rate.
Thus, from the point of view of infrastructure development and production technology the process of development of gas and gas condensate fields is divided into two periods: natural pressure and artificial lift production. The difference between these two periods lies in usage of a compressor unit designed for increase of the produced gas pressure to values required both at inlet of the treatment plant (in order to ensure the working parameters of the gas treatment process) and for further supply into the trunk gas pipeline. This unit is called a booster compressor station (BCS). As a rule, it is located at the site adjacent to the GTP site ( Compression of gas for its downstream transportation; Maintaining of the required gas pressure at the GTP inlet.
Compression of gas for its downstream transportation;
Maintaining of the required gas pressure at the GTP inlet.
Thus, BCSs are used for extension of the stable gas production period at gas and gas condensate fields where formation pressure is decreased to the point at which pressure in the field gathering main pipeline, at GTP and in trunk gas pipeline restricts flow rates of the wells. In other words, BCS allows to maintain the GTP capacity at the designed level and to increase gas recovery factors as decreased pressure at the BCS inlet may be used for wellhead pressures decrease and increase of flow rates.
For modern day reservoir simulators, it is essential to provide realistic physical description of reservoirs, fluids and hydrocarbon extraction technology and guarantee excellent performance and parallel scalability.
In the past, the advances in simulation performance were largely limited by memory throughput of CPU based computer systems. Recently, new generation of graphical processing units (GPU) became available for general purpose computing with the support of double precision floating point operations, necessary for dynamic reservoir simulations. The graphical cards currently available on the market have thousands of computational cores that can be efficiently utilized for simulations.
In this paper, for the first time we present results of running full physics reservoir simulator on CPU+GPU platform and discuss implications of this modern technology on the existing reservoir simulation workflows. We discuss challenges and developed solutions for running reservoir simulations using modern CPU+GPU hardware architecture and propose a methodology to distribute the workload between various parts efficiently. The approach is tested on several data sets on various computational platforms, such as personal computers and clusters with and without GPU's involved.
The technology proposed in this paper demonstrates multifold speed up for models with substantial number of active grid blocks. The speed up due to GPU utilization can in some cases reach as high as 3-4 times compared to the traditional GPU-based approach. Considering the recent progress in the GPU development, this factor is expected to grow in the near future, and the hybrid CPU+GPU based approach allows to utilize the exciting potential of the hardware evolution. The results, advances and potential bottlenecks combined with detailed analysis of the performance and the ‘value for money’ of the modern hardware solutions are discussed.
We TTI reverse time migration is an important method for introduce random velocity boundary conditions to achieve complicated structures. However, it is not widely applied to GPU implementation. Meanwhile, we adopt multiple seismic data processing. Computation efficiency is an asynchronous streams with multi-GPUs to improve important constraint. We use GPU with CUDA instead of concurrency without ignoring GPU bandwidth as far as traditional CPU architecture. To accomplish this, we possible. We also discuss the computational efficiency with introduced a random velocity boundary in the source our algorithm. Finally, we apply it to our model and present propagation.This process avoids large storage memory and the correct implementation of the TTI RTM and its IO requirements, which is important when using a GPU advantages over isotropic RTM. with limited bandwidth of PCI-E.
Tsunamis generated by earthquakes generally propagate as long waves in the deep ocean and may be mathematically described by the shallow water equations (SWEs). Tsunami propagation and inundation usually involve a vast problem domain, which requires a highly efficient numerical model to provide accurate predictions. In this work, a hydrodynamic model that solves the 2D SWEs using a finite volume Godunov-type shock-capturing scheme is comprehensively tested on different hardware devices, covering both Central Processing Units (CPU) and Graphics Processing Units (GPU), for efficient tsunami modeling.
Tsunamis may cause huge loss of lives and economic damage as evidenced by the 2004 Indian Ocean event and the 2011 Japan event. Numerical prediction of the tsunami propagation and inundation provides essential information for evacuation management, risk assessment, city planning and structural design. Numerical models are also an indispensable component in most of the tsunami forecasting and warning systems.
Tsunami propagation and inundation can be mathematically represented by the shallow water equations (SWEs) or Boussinesq equations with an acceptable level of accuracy. Most of the prevailing tsunami models solve the SWEs or Boussinesq equations using finite difference methods (FDM) (Imamura, 1996; Titov and Synolakis, 1995), finite volume methods (FVM) (Leveque et al., 2011), finite element methods (FEM) (Tinti et al., 1996) or smoothed particle hydrodynamics (SPH) (Benedict and Robert, 2008). However, a tsunami event usually takes place in a vast domain and assessment of tsunami impacts may need multi-scale simulations that can accurately predict wave propagation across the ocean as well as inundation in urban areas requiring high-resolution representation of the topographic features. The high computational demand of this type of modeling exercises hinders wider application of most of the existing tsunami models.
In order to improve the computational efficiency of tsunami models to facilitate multi-scale simulations, different approaches have been widely reported in literature, including adaptive mesh refinement (e.g. Leveque, et al., 2011; Popinet, 2011) and parallel computing (e.g. Lavrentiev-jr et al., 2009; Pophet et al., 2011). In recent years, attempts have also been made to explore the potential of the graphics processing units (GPU) for improving model performance. GPU accelerated models have been presented in computational biophysics (Owens et al., 2008), computational fluid dynamics (Crespo et al., 2011), computational hydraulics (Brodtkorb et al., 2012; Smith and Liang, 2013), among other fields. More recently, authors have also attempted to develop CUDA-based GPU models (Vazhenin et al., 2013; Amouzgar et al., 2014) for tsunami simulations to further demonstrate the potential of this modern high-performance computing technology. However, the model performance across different devices has not yet been adequately compared to fully justify the benefit of this new development.
Liu, Xiaobo (The University of Tulsa) | Chen, Jingyi (The University of Tulsa) | Lan, Haiqiang (The University of Tulsa) | Zhao, Zhencong (The University of Tulsa) | Zhao, Tao (The University of Tulsa)
In seismic exploration, seismic wavefield simulation with irregular free surface provides important information for interpreting the characteristics of seismic wave propagation. In this study, the free surface boundary conditions are accurately applied by introducing a discretization that uses a boundary modified difference operator for the mixed derivatives in the governing equations. To suppress the artificial reflections at the truncated boundaries, the convolutional perfectly matched layer (CPML) boundary condition is successfully applied for seismic wave field propagation with irregular free surface in elastic isotropic media. The results show that CPML can be successfully inserted into seismic wave equations with irregular free surface and proved to be more efficient in suppressing artificial reflections. Additionally, GPU (Graphic Processing Unit) parallel computing was used to accelerate computation of large scale finite difference of seismic wave propagation with irregular free surface.
It is quite beneficial for us to model seismic wave propagation in elastic, isotropic media with irregular topography. In the last two decades, several researchers have introduced various approaches to simulate seismic wave propagation in elastic media with irregular surface (Toshinawa and Ohmachi, 1992; Komatitsch and Vilotte, 1998; Galis et al., 2008). Nilsson et al. (2007) presented a stable discretization of the free surface boundary conditions by using boundary-modified difference operators. Appelo and Petersson (2009) proposed a stable discretization in the curvilinear coordinate systems to handle the free surface boundary conditions. They discretized the irregular free surface boundary condition in the curvilinear coordinates to deal with 2D isotropic media. Lan and Zhang (2011) developed the elastic wave equations in the curvilinear coordinate system for heterogeneous transversely isotropic media by using a stable and explicit second-order accurate finite-difference scheme.
An efficient absorbing boundary condition is needed to eliminate the artificial reflections. Berenger (1994) first introduced a new absorbing boundary condition called the perfectly matched layer (PML). For PML, the waves with grazing incidence cannot be absorbed completely. These grazing incidences do not penetrate very deep in the PML absorbing layer. The Convolutional Perfectly Matched Layer (CPML) was first proposed for electromagnetic media by Roden and Gedny (2000). It proved to be highly effective at absorbing artificial reflection waves, especially for long time signatures, surface waves and elongated domains of calculation (Roden and Gedny, 2000). Originally, the CPML was introduced in the first order formulation, Li and Matar proposed to extend it for a second-order system, which described the elastic waves using displacement formulation (Li and Matar, 2009). Lan et al. (2015) applied the PML to seismic wavefield simulation with an irregular free surface. In this research, it is the first time that CPML boundary condition was successfully implemented for wavefield propagation with irregular free surface in the second order system.
Geomechanical models of commercial reservoirs comprise hundreds of thousands to millions of grid cells. These lead to large systems of linear equations. The solution of these systems is time consuming and, in most cases, dominates the total runtime of geomechanical simulations (70 to 80% of the total runtime). In this paper, we will present a solution for accelerating the linear solver by combining a state of the art deflation algorithm with GPU technology to achieve a speed-up of 4 to 5 times for geomechanical simulations. In this paper, we will include details of both the deflation algorithm for geomechanics and our GPU implementation. We will conclude by presenting the numerical results obtained.
Owe to the irregularity, there are mainly two challenges to accelerate unstructured grid-based numerical methods on Numerical methods based on structured grid can be more graphics processing units (GPUs): race condition and easily ported to GPU, which have a regular data access global memory coalescence. We propose a scheme pattern, such as the typical regular grid finite difference composed of three parts to tackle these two problems: method (Abdelkhalek et al, 2009;. Micikevicius et al, firstly apply centroidal Voronoi tessellation (CVT) method 2009.), while unstructured grid-based methods, having to optimize the grid, relaxing the irregularity, secondly random-like data access patterns, are not well suited to develop a novel coloring method to avoid race conditions, GPU. Computations based on unstructured grid have a thirdly develop a renumbering method of cells and vertexes typical pattern: firstly gather data, then compute, and the to increase the global memory coalescence. We use the resulting data is reduced and scattered finally. Take finite acoustic grid method to demonstrate the efficiency of our element method (FEM) for example, gather nodal data for scheme, which also applies to other numerical methods each element at first, then compute element contributions to based on unstructured grid.
Inoue, Nelson (GTEP/PUC-Rio) | da Fontoura, Sergio Augusto Barreto (GTEP/PUC-Rio) | Albuquerque, Rafael Augusto do Couto (GTEP/PUC-Rio) | Lautenschläger, Carlos Emmanuel Ribeiro (GTEP/PUC-Rio) | Righetto, Guilherme Lima (GTEP/PUC-Rio)
The present work presents the implementations of a process developed to evaluate the geomechanical effects in petroleum reservoirs and their adjacent rocks. This process can be divided in four parts: (i) workflow for performing the analyses including the pre-processing (mesh generation of a finite element model and the assembly of the input file for the finite element analysis, to run the coupling program), and the post-processing (visualization of the results from reservoir simulation and stress analysis), (ii) a partial coupling scheme, (iii) a partial coupling program, and (iv) a finite element program on GPU. Part (i) of the process was implemented in Gocad (Geological Object Computer Aided Design) program as a plug-in to make sure the geological aspects of the field can be honored in the finite element model. In Part (iv) a finite element program on GPU (Graphics Processing Unit), called Chronos, was implemented in order to reduce the simulation time. The code was written considering optimized parallel algorithms for assembling the global and local stiffness matrix as well as the solution of the linear equation system through of the conjugate gradient method. The results showed significant reduction in the processing time of the finite element analysis when compared with the conventional approach performed in CPU. The plug-in allows a better handling of the input and output data and to run the coupling program. These features allow the engineers to run a stress analysis coupled with a reservoir simulation in a simple and intuitive way, with low computational costs.
Tsunamis generated by earthquakes generally propagate as long waves in the deep ocean and develop into sharp-fronted surges moving rapidly towards the coast in shallow water, which may be effectively simulated by hydrodynamic models solving the nonlinear shallow water equations (SWEs). However, most of the existing tsunami models suffer from long simulation time for large-scale high-resolution real-world applications. In this work, a graphics processing unit (GPU) accelerated finite volume shock-capturing hydrodynamic model is presented for efficient tsunami simulations. The model is demonstrated to consistently save approximately 40 times of computational cost for all of the benchmark tests.
The article discusses a high accuracy seismic modeling and reverse time migration (RTM) method. High-order finite-difference (FD) equation is used for modeling and RTM with fourth-order in time domain, eighth-order in x, y direction of space domain and sixteenth-order in z direction. This high-order FD solution can effectively reduce numerical dispersion. PML absorbing boundary conditions is used to effectively solve artificial boundary reflection problem. Thereby, the accuracy of modeling and RTM are significantly improved. By the advantage of GPU, the computation efficiency is largely increased. Research of theoretical data and real data shows this method is very applicable to the modeling and imaging for the media with complex surface and complex underground structure.