Integration of a Field Surface and Production Network With a Reservoir Simulator

Hepguler, Gokhan; Barua, Santanu; Bard, Wade

doi:10.2118/38937-pa

Cited by 55 publications

(33 citation statements)

References 9 publications

(6 reference statements)

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“…If surface facilities need to be included in the reservoir model, the solution when using Eclipse is to model each individual pipeline as an hydraulics table relating the inlet and and outlet pressure according to Eq. 2: (2) ) , , , A specific option in Eclipse (NODEPROP keyword -add lift gas option) allows to add the gas lift from the corresponding group subordinate wells to the produced gas entering the network. The optimizer will optimize the gas lift allocations at each well.…”

Section: Eclipse Tm Simulator (Sis)mentioning

confidence: 99%

Comparisons of Various Algorithms for Gas-lift Optimization in a Coupled Surface Network and Reservoir Simulation

Samier

2010

SPE EUROPEC/EAGE Annual Conference and Exhibition

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Gas lift is used for gas-liquid two phase producers to boost the production. Increasing gas liquid ratio GLR reduces the average fluid mixture density in the well connections and therefore reduces the hydrostatic pressure drop and hence reducing the bottomhole pressure resulting in a higher production rate or a longer individual well production period. This technique is also used for deep offshore fields injecting the gas at the toe of the FPSO risers located at the seafloor.But as the lift gas supply is increased further, friction pressure losses in the tubing or the riser become more important and the production rate peaks then starts to decrease. Also high gas flowrates may induce corrosion problems, and the total amount of available gas-lift is limited. Therefore an optimal gas-lift rate exists for a maximum production rate or more generally a maximum production profit.Various gas lift optimization algorithms have been proposed in literature for optimizing gas-lift to individual wells or within a group of wells, very few are suitable for long-term reservoir development studies with gas-lift injection within a network (FPSO riser toe for example).Commercial simulators such as Eclipse, VIP, Nexus, … provide internal optimization tool which are convenient for gas-lift at wells connections. Optimizing gas-lift within a network with additional gas rate inside flowlines or risers becomes much more complicated since the THP limits of all the other wells in the network are affected. Each time a lift gas increment is added or substracted, the whole network must be rebalanced with the appropriate lift gas rate in order to recomputed the change in the field oil production rate. The paper reviews some of the optimization methods available in commercial coupled surface network and reservoir simulators such as Resolve -Gap-Eclipse, Nexus, Avocet, … Several optimization algorithms linked to a surface facility model coupled to an open reservoir simulator prototype have been also applied (Ensemble based method, Steepest-Descent, Gauss-Newton, BFGS, ..) and compared to previous commercial software solutions.Results of the comparisons are presented on a surface network model coupled to a reservoir simulator where the objective is to optimize the gas-lift allocations at riser toes.One of the test cases based on a modified SPE 9 comparative test is fully documented and allows the readers to compare results with their own optimization algorithm. Introduction Problem statementThe optimization problem is to maximize daily hydrocarbon production by optimally selecting lift-gas rates subject to the pressure and rate constraints of surface facilities. The problem has been addressed by several authors in the oil industry. Fang and Lo 1 proposed a linear programming technique to allocate lift-gas rates. Hepguler et al. 2 uses a sequential programming (SQP) optimization algorithm. Wang et al. 3 continued on the Fang and Lo's work. The optimization step is invoked at the Newton iteration level of a reservoir simulator and becomes a part of...

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Section: Eclipse Tm Simulator (Sis)mentioning

confidence: 99%

Comparisons of Various Algorithms for Gas-lift Optimization in a Coupled Surface Network and Reservoir Simulation

Samier

2010

SPE EUROPEC/EAGE Annual Conference and Exhibition

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“…Assisted History Matching for Surface Coupled Gas Reservoir Simulation D. Biswas, SPE, SiteLark LLC Hepguler et al 3 presented their efforts in coupling Eclipse reservoir simulator to network simulator and optimizer (Netopt) where communication between these two simultaneously running simulators was achieved using Parallel Virtual Machine (PVM) message passing interface. Their overall system distinguished itself from the previous ones in terms of absence of any restrictions in the boundary conditions imposed.…”

Section: Spe 101233mentioning

confidence: 99%

Assisted History Matching for Surface Coupled Gas Reservoir Simulation

Deepankar¹

2006

SPE Asia Pacific Oil &Amp; Gas Conference and Exhibition

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TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractFor a gas reservoir, the intake pressures are available at a delivery point and the operator is obligated to supply gas honoring such downstream pressure requirements. As a result, it is imperative that the reservoir deliverability prediction be coupled with the pressure drop in the surface network. Additionally, this coupled system should not only honor the imposed delivery point pressure constraints but also the historical attributes of pressures and rates. In this paper, a modified Gauss-Newton method is utilized in conjunction with a non-linear parameter estimation algorithm to history match a surface-reservoir coupled gas reservoir simulation.Control Volume Finite Element (CVFE) based reservoir simulator is amenable to unstructured grids to resolve near wellbore and high activity (high permeability channels, fractures) flow areas. The pressure drop in the surface network is modeled using Weymouth's equation of steady state pipeline flow. More importantly, the total system is solved in a coupled fashion thereby enabling the solution to be controlled by surface pressure constraints. In addition, both surface and reservoir decision variables are estimated using a modified Gauss Newton algorithm in the assisted history matching step.Examples from dry gas reservoir demonstrate the usefulness of this methodology. First, the necessity of coupling surface and reservoir models is highlighted. Next, the computational efficiency of the assisted history matching algorithm as compared to perturbing critical reservoir and surface attributes in a heuristic manner is underscored.There are three significant contributions of this paper, namely (a) an assisted history matching algorithm proves efficient in comparison to arbitrary perturbation of decision variables (b) a coupled reservoir-surface model renders a more accurate pressure prediction of the total system and finally, (c) an unstructured grid simulator provides the platform for accurate and cost-effective reservoir modeling alternative.

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“…The first coupled compositional simulation was presented by Litvak and Darlow (1995) with a commercial reservoir simulator. They also described an implicit scheme in which the reservoir and surface network were solved simultaneously by treating the network nodes as additional gridblocks of the reservoir model.…”

Section: Introductionmentioning

confidence: 99%

A Semi-Implicit Approach for Integrated Reservoir and Surface-Network Simulation

Liang¹,

Rubin²

2014

SPE Reservoir Evaluation &Amp; Engineering

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Conventionally, methods of coupling reservoirs and surface networks are categorized into implicit and explicit approaches. The term "implicit coupling" indicates that the two simulators solve unknowns together, simultaneously, or iteratively, whereas "explicit coupling" indicates that the two simulators solve unknowns sequentially and exchange their boundary conditions at the last coupled time t n .The explicit approach is straightforward to implement in existing reservoir and surface-network models and is widely used. Explicit coupling does have drawbacks, however, because well rate and pressure oscillations are often observed.In this paper, a new semi-implicit method for coupled simulation is presented. This technique stabilizes and improves the accuracy of the coupled model. The "semi-implicit coupling" overcomes the problems found in explicit-coupling methods without requiring the complexity of a fully implicit coupled model.The new approach predicts inflow-performance-relationship (IPR) curves at the next coupled time t nþ1 by simultaneously conducting well tests for all wells in the reservoir before actually taking the required timestep. All wells first flow simultaneously to the next coupled time t nþ1 with the well rates unchanged from the last coupled timestep. The timestep is rewound, and all well rates are reduced by a uniform fraction and then simultaneously flow again to t nþ1 . By extrapolating the resulting well pressures, the well's shut-in pressures at time t nþ1 are determined, and thus, straight-line IPRs are produced. The new IPR curves approximate better each well's drainage region at t nþ1 and each well's shut-in pressure at t nþ1 which helps to stabilize the explicitly coupled model.The new coupling technique normally does not require iteration between the reservoir and surface network and normally has the stability and accuracy characteristics of an implicitly coupled approach. Because the well tests already account for individual well-drainage regions, an explicit knowledge of the well-drainage region is not required. Because of the stabilized IPR, the approach also was found to reduce the overall computational time compared with explicit coupling.Applications of the new approach are presented that show significant improvements surpassing explicit coupling in both stability and accuracy. IntroductionIt has been widely recognized that when reservoir-deliverability forecasting and surface-network planning are required, integrated reservoir and surface-network simulation can provide more-realistic results than separate models of the reservoir and surface network. During the last 40 years, different methods to couple reservoir and network models were developed and studied by a number of investigators. Dempsey et al. (1971) first presented a technique that iteratively solved reservoir, tubing-string, and gathering system models to accurately evaluate gasfield deliverability. The concept was extended to the black-oil system by Startzman et al. (1977), and the scheme was modified by Emanuel and ...

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Integration of a Field Surface and Production Network With a Reservoir Simulator

Cited by 55 publications

References 9 publications

Comparisons of Various Algorithms for Gas-lift Optimization in a Coupled Surface Network and Reservoir Simulation

Comparisons of Various Algorithms for Gas-lift Optimization in a Coupled Surface Network and Reservoir Simulation

Assisted History Matching for Surface Coupled Gas Reservoir Simulation

A Semi-Implicit Approach for Integrated Reservoir and Surface-Network Simulation

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