Accurate and robust well modeling is essential for performing reservoir simulations of practical interest. The Multi-Segment well (MSWell) model is able to describe the well topology and accurately represent the multiphase multicomponent flow and transport behavior in the wellbore. The fully coupled method (FC) has been developed and widely applied on coupled reservoir and MSWell modeling due to its unconditional stability and consistent implementation. A local well solver can be applied to provide a better nonlinear precondition for MSWell variables in order to accelerate the nonlinear convergence of the FC method.
However, solving the coupled MSWell and reservoir model in a fully implicit scheme can still present limitations on some practical applications. First, the well or surface facility solver can be separate from the existing reservoir simulator, making it challenging to employ the fully implicit method. Second, complex linear and nonlinear solvers need to be designed to pair the specific wells and reservoir models. These solvers have to account for the different flow characteristics and discretization domains between reservoir and MSWell. A sequential coupling scheme can become preferable in such situations.
Sequential fully Implicit method (SFI) splits the fully coupled reservoir and MSWell equations into two parts and solves them sequentially. In spite of accomplishing an implicit coupling in a sequential scheme, SFI suffers the slow outer loop convergence rate especially when reservoir is strongly coupled with the wells, which is very often the case. The slow convergence is caused by the linear convergence rate of the fix point iteration used in the SFI. Here, we developed a sequential implicit Newton's method (SIN) for coupled MSWells. SIN incorporates a Newton update at the end of each sequential step to achieve a quadratic convergence of outer iterations, while require a limited extra computational cost. Numerical results show that SIN attains comparable nonlinear Newton iterations with the FC in the coupled heterogeneous reservoir and complex MSWell problems.
Integrated simulation of reservoirs, wells, and surface facilities is becoming increasingly popular for modeling hydrocarbon production from deep offshore assets. Currently, there exist two common approaches for the integration. The first approach employs separate reservoir and facility simulators; whereas, the second approach combines the two within one reservoir simulation framework. Both approaches have advantages and drawbacks. For example, the first approach can be more accurate for the facility modeling, but overall it suffers from stability issues and long running times. On the other hand, the second approach is always numerically stable and typically provides better runtime performance, but requires additional inputs, e.g., Vertical Lift Performance (VLP) tables. Preparation of these additional inputs can be time consuming and often error-prone. Moreover, the VLP tables used in the second approach are typically constructed with the averaged values of "auxiliary" parameters, such as inlet temperature, water salinity, etc. This averaging can potentially lead to inaccuracies during simulation.
In this paper, we propose a new framework for integrated asset modeling which combines the benefits of the two approaches and hence significantly improves the efficiencies in both workflow construction and simulation accuracy. Our framework is based on the previously presented fully coupled network approach implemented as an in-house extension to a reservoir simulator. Here we extend the approach by introduction of an additional coupling step with a separate pipe flow (network) simulator. However, instead of using the pipe flow simulator to solve the network, it is used only to dynamically generate the VLP tables for the simulator's internal network module. Comparing to the previous fully coupled network approach, our new approach streamlines the simulation workflow by avoiding the necessity of the additional manually created network input. Furthermore this new approach also improves the modeling accuracy by using a generalization of the VLP description (e.g. with temperature as additional dimension) and by avoiding tables extrapolations. In this paper we discuss the new workflow and the new dynamic generalized VLP table construction in details.
Darche, Gilles (Total SA) | Marmier, Rémy (Total SA) | Samier, Pierre (Total SA) | Bursaux, Romain (Total SA) | Guillonneau, Nicolas (Total SA) | Long, Jérôme (Total E&P Congo) | Kalunga, Hernani (Total E&P Angola) | Zaydullin, Rustem (Total E&P Research & Technology USA) | Cao, Hui (Total E&P Research & Technology USA)
We present a global simulation strategy of coupling reservoir and surface network models to manage production profiles of a deep-offshore field (West Africa) operated with a subsea development. This strategy allows a better consolidation of both short-term and long-term production profiles as compared to stacked standalone reservoir profiles.
The simulation study consists of 4 independent reservoir models, connected to surface facilities through a common subsea network. The first method uses loose external coupling between a new-generation commercial reservoir simulator and a commercial subsea network modeling package. It will be used to derive an optimal management of the network (network design, surface controls). This first coupling approach can also generate input data (pressure drops in network described by VLP tables) necessary for the second coupling approach, consisting in a fully coupled reservoir-surface simulator developed in-house, used to evaluate infill scenarios and to compute long-term production profiles.
These two coupling approaches bring their own value to the evaluation of the potential of the field.
The loose external reservoir-network coupling better manages surface constraints. It enables to design and to optimize the subsea network, accounting for the surface capacities. It also manages transient effects in the network, therefore enabling short-term optimization of the production. It will also highlight critical features (like pipe erosion, managed through the C-factor parameter) for the network.
However due to high TCPU and numerical instability, it is unsuitable for extensive sensitivity studies. For that, we use our in-house fully coupled reservoir-network simulator, with network description provided through the external coupling approach. These fully-coupled simulations, though using simpler network descriptions, are much faster and more robust, enabling to perform sensitivities on reservoir management, on infill well scenarios, in order to maximize long-term production profiles. We also developed new options in our in-house simulator to model the critical network features identified by the external coupling approach (like C-factor, fluid mixing, gas-lift optimization on risers).
Therefore, the use of these two workflows has enabled a full optimization of the field development, both The study has shown that these two technical coupling approaches are complementary, and bring better value to a field development when performed together. Furthermore, the external coupling approach identified the critical network features to be also managed in a fully-coupled reservoir-surface simulator, leading to new developments into this simulator (management of C-factor, fluid mixing, gas-lift optimization on risers).
The paper proposes a novel framework for the reservoir and surface facilities modeling. Our new approach benefits from the advantages of the two previous approaches: numerical stability/efficiency of the fully coupled approach and the workflow/accuracy of the separated approach.
Coupled reservoir flow and geomechanics has numerous important applications in the oil & gas industry, such as land subsidence, hydraulic fracturing, fault reaction and hydrocarbon recovery etc. High fidelity numerical schemes and multiphysics models must be coupled in order to simulate these processes and their interactions accurately and efficiently. Specifically, in the applications of CO2 sequestration, the effect of geomechanics on carbon storage estimation is not negligible. However, coupled flow-geomechanics simulations are very computationally expensive and most of the computational time is usually spent for geomechanics calculations. This paper investigates a three-way coupling algorithm that uses an error indicator to determine when displacement must be updated and whether fixed-stress iterative coupling technique is required. Numerical experiments with coupled nonlinear single-phase flow and linear poromechanics shows that the three-way coupling algorithm can speed up 4 times comparing to fixed-stress iterative coupling algorithm. Extensions to coupled compositional flow with poromechanics also shows a speed-up for 5 times for continuous CO2 sequestration applications and 2 times for surfactant-alternating-gas applications (SAG). The substantial speed up makes the three-way coupling algorithm of flow and geomechanics feasible in the large-scale optimizations. Based on the three-way coupling of compositional flow and geomechanics, we experimented two black box optimization algorithms, covariance-matrix adaptation evolution strategy (CMA-ES) and genetic algorithm (GA), for the optimization of well controls during SAG process to maximize CO2 storage volume. CMA-ES outperforms GA in that it is more robust, and it achieves higher objective function value in less simulation runs. The optimized SAG process achieves 27.55% more CO2 storage volume and reduces water and surfactant consumption by 54.84%.
Steam-Assisted Gravity Drainage (SAGD) is one of the popular methods for heavy oil production. The process is efficient and economical. However, it requires the use of large quantity of water and disposal of waste water can be costly. In addition, burning of natural gas for steam generation contributes to additional carbon dioxide generation, a known greenhouse gas, which is also undesirable. A method to heat up the in-situ oil without the use of injected water is highly desirable. Radio frequency (RF) heating of heavy oil reservoir is a potential method for oil recovery without steam injection. The evaluation of the potential of such method requires the coupling of a reservoir simulator with an electromagnetic (EM) simulator.
This paper describes the development and implementation of a flexible interface in a reservoir simulator that allows the runtime loading of third party software libraries with additional physics. Data is exchanged between the reservoir simulator and externally loaded software libraries through memory, therefore there is minimal communication overhead. The implementation allows for iterative coupling, explicit coupling and periodic coupling. This paper describes the mathematical coupling of the mass and energy conservation equations in the reservoir simulator with the Maxwell equations in an external library. The electromagnetic properties in the reservoir are highly dependent on temperature and water saturation, this dependence is accounted for in the coupled code using table look-up properties.
Canadian heavy oil and reservoir properties were used in our simulation investigation. We found that RF heating alone can be effective in heating up the in-situ water and reducing heavy oil viscosity by several orders of magnitude. As the in-situ water near wellbore was vaporized by RF heating, electrical conductivities were reduced to zero and thus allowed the EM wave to propagate further into the formation and heat up the water further away from the wellbore. With properly designed RF heating field pilots and tuning of EM and reservoir parameters, the coupled reservoir/EM simulator can be a powerful tool for the evaluation and optimization of RF heating operations.
The interface is sufficiently flexible to allow different types of multi-physics coupling. In addition to RF heating, it has also been used for reaction kinetics and geomechanics coupling with a reservoir simulator. It has been used for large scale coupled full field simulation with over 30 million cells.
The objective is to couple tens of full-field giant reservoirs and apply optimized-based well management system to the all the flowing wells to manage a high level production plateau and injection system.
In this work each individual reservoir simulation model is a giant field, with a large historical (70y) and prediction (200y) time periods, 10s of millions of cells and thousands of wells, many injection and production constraints and drilling targets. Each of these giant fields requires a parallel supercomputer to run each individual model in a reasonable time. To couple many of these models they are all executed as one combined parallel job, which is subdivided in groups of processes dedicated for individual reservoirs. A layered communication hierarchy is used, which facilitates coordination and synchronization of the individual reservoirs and the optimization and allocation of the production and injection targets of every well and group of wells in the coupled system. Great effort was placed on making the user workflow very simple; having established a history and prediction field-scale model, the coupling can be achieved by a straightforward manipulation of the individual field-scale models, and high-level constraints and targets can be added to the coupled system. To alleviate some run time/resource issues, the level of detail required for each model was chosen by activating a coarsening facility within the reservoir simulator. This reduced the simulation resources needed for individual fields, but exacerbated the potential bottleneck of the optimization engine, as all well and group constraints were preserved in the coupled model.
To stress test this system, up to 15 giant models were coupled, with over 15 thousand wells managed by an optimized based well management system. The single node responsible for allocation of all the wells was not found to be a bottleneck in the system.
The journey from the detailed full-field giant model to a coupled super-giant coupled model has many challenges. Here, these are alleviated by tight and efficient integration of the coupling optimized-based well management system and the massively parallel reservoir simulator. This paper demonstrates a new industry high water mark for the coupling of reservoir models.
Tang, Xuanhe (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University) | Zhu, Haiyan (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University & State Key Laboratory for Geomechanics and Deep Underground Engineering, China University of Mining & Technology) | Liu, Qingyou (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University) | Song, Yujia (State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University)
To investigate the time-lapse, three-dimensional (so-called four dimensional/4D) stress during production/injection, a 4D multi-physical modeling method is proposed. A finite difference method (FDM) reservoir simulator is used to couple thermal-hydrological-chemical (THC) processes, while a finite element method (FEM) geomechanical simulator takes on the role of a thermal-hydrological-mechanical (THM) coupling calculator. Heterogeneity and anisotropy of the reservoir flow and geomechanical properties as well as the permeability stress-sensitivity can be considered in modelling based on field and experimental data. In order to couple the flow model with the geomechanical model, an improved interface (coupling) Python code is provided to communicate data between the finite difference (FD) and finite element (FE) grids. Ultimately, this method is applied to analyze the stress and poro-elastic parameters evolution of hydraulic fractured Sichuan Basin shale gas reservoir and Qinshui Basin coalbed methane (CBM) reservoir in production.
Rasoanaivo, Ombana (TOTAL S.A.) | Danquigny, Jacques (TOTAL S.A.) | Henry, Pierre (Petroleum Experts) | Hopkinson, David (Petroleum Experts) | Liu, Adeline (TOTAL E&P) | Marty, Jacques (TOTAL S.A.) | Marmier, Rémy (TOTAL E&P)
Using a software integrator, a commercial reservoir simulator is tightly coupled with a commercial Transient Well Model. This is required when transient reservoir behaviour interacts with transient wellbore phenomena. It is the case in a tight gas field which is being developed since 2012 in China; long natural cycles of gas production in liquid loading regime followed by period of low or quasi nil-gas production are observed. Cyclic production is also being implemented to optimize the average gas production. In both cases, usual decline curve analysis is no longer valid. And computing long term production forecast becomes a challenge. The innovative application presented in this paper is an optimization of Cyclic Production in Liquid Loading Regime of a tight gas reservoir by coupling transient modelling of reservoir and wellbore.
A workflow is implemented in the software integrator RESOLVE which enables the coupling between a well and its multiple hydraulically fractured reservoirs. It ensures consistent results between the reservoir model and the transient well model in terms of mass flow rate, transient inflow performance and bottom hole flowing pressure. It also enables to visualize the cross-flow which occurs between the two reservoirs, and some water imbibition into the matrix during shut-in periods.
Tested on various reference wells, this new methodology represents properly the historical behaviour of the wells during steady-state flow and during self-killing periods. When modelling cyclic production, various shut-in / restart criteria can be handled by the workflow. It enables to optimize the average production of the wells and deliver some guidelines to the field operation teams. This is a great achievement compared with the need to implement long "cyclic production testing" campaigns.
Also, two-month coupled cyclic production modelling is performed at regular yearly intervals. Combining these long term production forecasts with the evolution of "average static pressure vs. cumulative gas production" derived from reservoir standalone long-term forecast, enables to compute reliable long term production forecast which accounts for cyclic production in liquid loading regime. The current results show significantly larger production than the one derived from usual decline curves.
Overall, the study is a leap forward in understanding transient well and reservoir interactions in order to improve field Estimated Ultimate Recovery. This field tested methodology can also be applied to many other situations when well instabilities interfere with reservoir transient behaviour (gas-lift heading, interference between unstable outflow and multi-layers inflow behaviour). To our knowledge, it is a "World First" of a coupling between a full commercial reservoir simulator and a commercial transient wellbore software.
Composite materials are good candidates for hydrofoils manufacturing, ensuring a good balance between strength and weight. In the high performances sailing yacht domain, hydrofoils are thin structures, highly loaded that experience significant displacements. This study investigates experimentally and numerically the influence of the laminate layup on the hydrodynamic performances of a surface piercing hydrofoil. Four hydrofoils with a constant chord, geometrically identical with different composite layups are mechanically characterized and tested in a hydrodynamic flume. The foils are designed to have a significant tip displacement of 5 to 10% of the span. Experimental results highlight a bending-twisting effect that leads to significant change in the hydrodynamic performances of the structures. Two different FSI numerical approaches: from a potential code coupled with beam theory to the full coupling of a shell structural code and a VOF hydro model with free surface are compared to the experiments with great results. The two approaches are two complementary bricks in the design process to compute the effect of passive deformation on hydrodynamic performances of the foils and therefore the yacht stability.
Liu, Yongsheng (China University of Petroleum, Beijing) | Gao, Deli (China University of Petroleum, Beijing) | Li, Xin (China University of Petroleum, Beijing) | Qin, Xing (China University of Petroleum, Beijing) | Li, He (China University of Petroleum, Beijing) | Liu, Hang (Yibin Natural Gas Development Company Limited)
Jet comminuting technology has proved to be an effective means of solid particle pulverization, and current research attempts to introduce it for drilling work to reduce cuttings size, because smaller cuttings are easy to circulate out of the bottom, thus can effectively prevent the formation of cuttings bed, especially in horizontal drilling. In this paper, the feasibility of cuttings’ comminution by jet is studied by means of numerical simulation with secondary development. The coupling analysis methods—including the computational-fluid-dynamics/discrete-element-model (CFD/DEM) modeling for the interaction between fluid and cuttings and the particle replacement and bonding modeling for cuttings breakage—are used to characterize the jet comminuting process of cuttings. Input parameters of simulation are reliable and verified by uniaxial compression tests. Case studies presented here indicate that cuttings can be considerably accelerated by 20 to 30 m/s through the throat, which provides a good effective speed for the cuttings. After being accelerated by the fluid and crushed with the target, the vast majority of cuttings results in smaller debris. Also, increasing the inlet speed affects the crushing efficiency. The inclination of the target at near 65 shows good results. This paper proposes a new perspective to introduce the jet comminuting technique for drilling operations, and its findings could help in guiding engineering design in the future.