Surface Pipeline Network Research Articles

Benchmarking study of coal seam gas production from Brownfield to Greenfield wells in the Surat basin, Australia

Benchmarking coal seam gas (CSG) production from Brownfield to Greenfield is an important step for assessing the development plan for Greenfield. However, the observed Brownfield production data is impacted by many factors besides reservoir properties, e.g., well spacing, well efficiency factor (WEFAC), surface pipeline network. This paper presents a case study in the Surat Basin to discuss how to benchmark CSG production from Brownfield to Greenfield. The selected Brownfield study area includes 143 wells and the Greenfield 450 proposed wells. Various tools for static modelling, decline curve analysis, and dynamic modelling were used in this study. Results show that the peak gas rate decreases quickly and the time to peak gas rate increases quickly when the WEFAC is less than 0.65. The peak gas rate is reached when the cumulative water production is between 39% and 46% of water-in-place for the selected box model. After introducing the wells’ online time ratio or WEFAC from the daily production data and the ratio of the observed cumulative water production to the expected cumulative water production, gas production rates can be predicted based on the modified Morse potential energy equation. Artificial neural networks (ANN) can be used to estimate the peak gas rate, the time to peak gas rate and the decline rate based on the reservoir properties; while the ramp-up rate can be calculated from the time to peak gas rate.

Coupled Modeling of the Surface Pipeline Network in a Low-Enthalpy Geothermal Field

This paper addresses the often overlooked, yet critical, aspect of designing and optimizing the surface pipeline network for the transportation of geothermal fluids from the wellheads to the delivery point, such as greenhouses, food drying plants, or fish farming units. While research on the geothermal industry predominately focuses on the reservoir and well engineering aspects of exploitation, insufficient attention has been given to the design of the pipeline network, leading to improper design and significant, yet avoidable, energy losses. Thus, this paper presents a comprehensive methodology for modeling and simulating geothermal fluid flow within the pipeline network by fully considering all hydraulic (friction, viscous flow, and gravity effects) and thermal (open air and underground pipeline heat loss) phenomena. These two aspects are handled simultaneously by setting up and solving the coupled set of the governing (differential) equations. We also demonstrate the difficulties that arise when attempting the solution of the mathematical problem, such as potential instability or lack of convergence. Finally, a fully detailed study of the real-world geothermal production system is presented utilizing the developed methodology to optimize the design and operation conditions of the system. By integrating debottlenecking strategies into the analysis, this approach not only maximizes power output, but also identifies and mitigates constraints within the system, ensuring efficient operation and performance increase.

Optimal design of the gas storage surface pipeline system with injection and withdrawal conditions

Abstract Underground natural gas storage (UNGS) is an important part of the natural gas supply system to ensure a balanced energy supply. The surface system, as an important part of the gas storage, undertakes the functions of gas injection and gas production of the gas storage, and its investment economy is of vital importance. In fact, the UNGS surface pipeline network has two-way injection and production characteristics, which is different from the one-way production characteristics of conventional oil&gas gathering and transportation systems. This paper takes the minimum investment of the pipeline network as the objective function, considers the gas injection and gas withdrawal flow conditions and esablishes a mixed integer non-linear programming model (MINLP) for the surface pipeline network of the UNGS to optimize its pipeline layout and diameter parameters. Constraints including the well affiliation, the number of stations, the gathering radius, the processing capacity and the flow/pressure equilibrium equations, are also taken into consideration. Taking an UNGS in China as an example, the results of the optimal structure and diameter of the pipeline network, as well as the pipe flow, node pressure, and maximum/minimum flowrate during gas injection and gas withdrawal are obtained. Finally, the effects of constraints such as processing capacity and radius on the structure layout and investment of the UNGS are analyzed, verifying the reliability and effectiveness of the model.

Layout optimization of tree-tree gas pipeline network

With the development of petroleum industry and the exploitation of unconventional gas reservoir, the topological form of surface pipeline network is changing gradually and a tree-tree structure is put forward in gas field. Therefore, optimization of the tree-tree pipeline network becomes urgent and indispensable. In this paper, a comprehensive optimization objective function and constraints is established to allow layout design. In view of the characteristics of the model comprising numerous discrete variables (e.g. location, number, allocation relationship, connection decision variable etc), a hierarchical optimization strategy is proposed to decompose it into three sub-problems. On the basis of the proposed model, an optimization program based on Delaunay triangulation has been presented to solve the non-linear constrained optimization problem which contains connection decision variable between wells in clusters on the constraint condition of path length restriction. Further, the reason of using Delaunay triangulation is analyzed and the optimization process of the essential sub-problem has been illustrated. Moreover, the developed program has been applied to a practical coalbed methane field project. The model and method in this paper is shown to be feasible and effective to solve layout optimization on two-level tree-tree pipeline network.

Coalbed Methane Production System Simulation and Deliverability Forecasting: Coupled Surface Network/Wellbore/Reservoir Calculation

As an unconventional energy, coalbed methane (CBM) mainly exists in coal bed with adsorption, whose productivity is different from conventional gas reservoir. This paper explains the wellbore pressure drop, surface pipeline network simulation, and reservoir calculation model of CBM. A coupled surface/wellbore/reservoir calculation architecture was presented, to coordinate the gas production in each calculation period until the balance of surface/wellbore/reservoir. This coupled calculation method was applied to a CBM field for predicting production. The daily gas production increased year by year at the first time and then decreased gradually after several years, while the daily water production was reduced all the time with the successive decline of the formation pressure. The production of gas and water in each well is almost the same when the structure is a star. When system structure is a dendritic surface system, the daily gas production ranked highest at the well which is the nearest to the surface system collection point and lowest at the well which is the farthest to the surface system collection point. This coupled calculation method could be used to predict the water production, gas production, and formation pressure of a CBM field during a period of time.

Gas Lift Optimization for Long-Term Reservoir Simulations

Summary Although various gas lift optimization algorithms have been proposed in literature, few are suitable for long-term reservoir-development studies, which require the gas lift optimizer to be highly efficient, flexible, and powerful enough to handle complicated fluid flows and operational constraints while having minimal impact on simulator convergence rates. This paper investigates methods to address these important issues. The gas lift optimization problem considered in this paper is to maximize daily hydrocarbon production by selecting optimally the well-production and lift-gas rates subject to pressure and rate constraints in nodes of the surface pipeline network (SPN) and to the amount of lift gas available. The problem is regarded as a well-management problem in a commercial reservoir simulator capable of simulating multiphase compositional fluid flow in reservoirs, well tubing strings, SPN systems, and separation facilities. The problem is solved in selected iterations of a reservoir-simulation timestep. This paper proposed a method for the described gas lift optimization problem and investigated its performance against multiple existing methods. Case studies showed that the new method is capable of producing high-quality results while requiring less CPU time for optimization and having a smaller impact on reservoir-simulator convergence. This paper also applied the concept of multiobjective optimization to smooth rate oscillations between adjacent iterations by sacrificing a certain amount of oil production. This method was proved to be successful in tested cases.

Gas Lift Optimization for Long-Term Reservoir Simulations

This article, written by Assistant Technology Editor Karen Bybee, contains highlights of paper SPE 90506, "Gas Lift Optimization for Long-Term Reservoir Simulations," by Pengju Wang and Michael Litvak, SPE, BP plc, prepared for the 2004 SPE Annual Technical Conference and Exhibition, Houston, 26-29 September. Although various gas-lift-optimization algorithms have been proposed in the literature, few are suitable for long-term reservoir-development studies that require the gas-lift-optimization process to be highly efficient, flexible, and sufficiently powerful to handle complicated fluid flows and operational constraints. These algorithms also must converge rapidly. The gas-lift-optimization problem considered in the full-length paper is to maximize daily hydrocarbon production by selecting the optimal well-production and lift-gas rates subject to pressure and rate constraints of the surface pipeline network and amount of lift gas available. Introduction When oil fields mature, oil production often is assisted by continuous lift-gas injection and constrained by the gas- and/or liquid-handling capacities of surface facilities. The optimal allocation of production rates and lift-gas rates is subject to reservoir deliverability and surface-facility capacities and other capital-investment decisions. Compared to real-time production optimization, the optimal rate allocation in long-term reservoir-simulation studies poses unique problems. Problem The optimization problem is to maximize the daily oil production by optimally selecting the well-production and lift-gas rates subject to surface-facility pressure and rate constraints. The optimization problem is considered a well-management problem in a commercial reservoir simulator capable of simulating multiphase compositional fluid flow in reservoirs, well tubing strings, surface pipeline-network systems, and separation facilities. Integration Procedure. The following is a procedure to integrate the optimization problem into the reservoir simulator. 1. Start with the pressure and fluid com-position in reservoir gridblocks calculated in the previous Newton iteration. Use well lift-gas rates from the previous Newton iteration as the initial guesses. 2. Solve the surface pipeline-network problem; convert pressure constraints to flow-rate constraints. 3. Perform production- and lift-gas-rate allocation optimization. 4. Determine active constraints in wells and nodes. Linearize multiphase-fluid-flow equations for well tubing strings and the surface pipeline network (numerical derivatives are used). Add these equations to the linearized fluid-flow equations for reservoir gridblocks. 5. Solve the linearized system of equations established in Step 4. 6. Repeat Steps 1 through 5 until convergence. 7. Advance to the next timestep.

Simplified Phase-Equilibrium Calculations in Integrated Reservoir and Surface-Pipeline-Network Models

Summary Effective procedures for the integrated reservoir and surface facility compositional simulations have been developed. Multiphase compositional fluid flow equations in reservoirs, well tubing strings, and surface pipeline network systems are solved simultaneously. The procedures have been implemented in the commercial compositional reservoir and surface facility simulator: VIP. The equation of state is applied for the phase-equilibrium calculations. A new equation-of-state (EOS) interpolation procedure has been developed (as an option) for simplified phase-equilibrium calculations in integrated compositional simulations. The EOS interpolation procedure can be effectively applied for phase-equilibrium calculations in reservoirs, well tubing strings, pipelines, and/or separators. Saturation pressure, recovery factors of hydrocarbon components, and compressibility factors are determined as tabular functions of pressure, temperature, and fluid compositions. The equation of state is applied for the automatic generation of these functions in an initialization step of a reservoir simulation. The effectiveness and accuracy of the new simplified phase-equilibrium procedure have been confirmed in many full-field compositional models and pattern models. The new option significantly reduces the central processing unit time required for the simulations and it matches results of fully compositional simulations in the tested models. The developed procedures for the integrated reservoir and facility compositional simulations have been applied in many reservoir studies. Their applications in the integrated reservoir and surface facility model of the giant Prudhoe Bay oil field have been demonstrated.

Optimal parameters design of oilfield surface pipeline systems using fuzzy models

Establishing and operating an oilfield surface pipeline system involves a large capital expenditure, which includes pipeline cost, power consumption cost, and thermal energy cost, etc. In this process, there exists a vast amount of fuzzy information, in both the objective and the constraint functions for an optimal design. System design based on such a huge volume of fuzzy information about multi-objectives and multi-constraints cannot be well handled by conventional mathematical tools. In this paper, a mathematical model from the fuzzy optimization approach is formulated for such oilfield surface pipeline systems. Both the multi-objective and multi-constraint functions are defined in a feasible fuzzy domain within the design parameters space. An optimal solution is selected from this domain for the design, for which the degree of expert satisfaction reaches the maximum. The methodology presented in this paper offers a new approach and a significant improvement of cost savings in the establishment and operation of an oilfield surface pipeline network system, beneficial for the oil industry.