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Iranian Maturity Model for the Assessment of Productivity System (iMAPS)
Die Fabrikplanung umfasst sowohl die Planung des Produktionssystems als auch die Auslegung des zugehörigen Industriegebäudes. Aufgrund von zunehmender Spezialisierung und Interdisziplinarität sowie hohem Zeit- und Kostendruck in einem dynamischen Projektumfeld sind Fabrikplanungsprojekte entsprechend durch eine hohe Planungskomplexität gekennzeichn...
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... The maximum oil production (production potential) delivered by the system upstream the subsea processing station is a function of the recovery factor (R f ) and the pressure at the suction of the subsea station (p s ) (Stanko 2021): ...
As the use of subsea processing increases and technology advances, subsea layout possibilities and configurations diversify and get more complex, causing manual design processes to be cumbersome and often suboptimal. Besides, most subsea layout and processing equipment design is done when there are still significant uncertainties (e.g. cost, oil price, reserves), which makes it challenging to define an optimal solution.
This thesis explores the use of model-based optimization and probabilistic analysis to provide decision support to field planners when designing offshore oil and gas systems. It can be divided into two parts: the first provides methods to determine main aspects of the field (e.g. production profile and drilling schedule) during early phases of field development, when there are considerable uncertainties. The second part of this thesis proposes methods to optimize subsea layout considering subsea processing, which is typically neglected.
To address the problem in the first part of this thesis, a deterministic non-linear model from the literature was taken as basis and optimizations were performed to determine the number of wells and plateau rate that maximize net present value considering varying levels of uncertainties. The uncertainties considered were oil price, oil in place, and well productivity. Two optimization methods were tested, one exact and one heuristic.
For the second part of the thesis, a mixed integer non-linear programming model is used to find optimal subsea layouts considering subsea processing. The model considers variation in reservoir deliverability and operating pressure for subsea equipment, besides estimating equipment cost, reliability and maintenance aspects, and pressure drop in discharge piping. A hybrid method is proposed to tackle large instances of the problem, combining a genetic algorithm for solving integer variables with a nested non-linear optimization for continuous variables.
... Although the estimation accuracy of the CAPEX model was found to be too high for it to be a reliable, generally the three developed proxy models can still be used with caution. Compared to the current proxy cost models by González, 2020;Stanko, 2020;Kuznetsov et al., 2011;and Shereih, 2016; the models developed in this study have considered the variability of DRILLEX with depth and number of the casing. The previous studies made unrealistic simplifications and assumptions whereby uniform costs were assumed for all drilled wells, an assumption that might not be always true. ...
Petroleum economic evaluation involves estimating revenues from forecasted production profiles and field costs including capital expenditures (CAPEX), drilling expenses (DRILLEX), and operating expenses (OPEX). The existing cost-estimating tool requires several inputs making it time-intensive and difficult to use with few data during the early stages of projects. Majority of the previously developed time saving cost estimations proxy models rely on unrealistic assumptions that include uniform operational costs for different fields with a different number of wells, casings, and drilled depths. This work focused at developing proxy models that consider the variability of the development costs with different parameters. The developed models benefited from a three-step approach for CAPEX, DRILLEX, and OPEX estimations based on datasets from three wells from a gas field in southern coastal Tanzania. Firstly, cost sensitivity analysis was performed using QUE$TOR v15.1.0.18, a cost estimating commercial software to determine the most influential field parameters of the field costs. Secondly, the field cost models were generated based on historical cost data from the gas field using multivariable regression analysis with the help of Statistical Package for the Social Sciences software (SPSS) v22.0. Lastly, errors analysis was done for checking the predictive reliability of the models. Based on the analysis, the CAPEX and OPEX were found to be strongly linearly dependent on the size of processing facilities, number of producing wells in the gas field and production capacity, respectively. On the other hand, a nonlinearity relation was revealed on of the DRILLEX which was strongly dependent on drilled well depth and number of installed well casing. Results show that the developed models are useful and their reliability becomes robust when more data is used. A stochastic modeling approach was further recommended for the models to incorporate uncertainties associated with the parameters used to quantify the cost estimates.
... The maximum oil production (production potential) delivered by the system upstream the subsea processing station is a function of the recovery factor ( ) and the pressure at the suction of the subsea station ( ) [15]: ...
Designing a subsea production system is a task that takes several months to complete by an experienced and multidisciplinary team of engineers. In this work, a computerized hybrid method to find optimal designs and support subsea production system design using a genetic algorithm combined with a gradient search method is proposed.
The genetic algorithm is formulated to optimize the structure of the production system, while the gradient method solves the continuous non-linear variables related to flow rates, reservoir deliverability, equipment capacities, and others. The study case is based on the Goliat field. This hybrid approach is compared with an exact method.
The hybrid method successfully finds subsea configurations that maximize the net present value in shorter running times when compared to an exact method. The methodology presented provides an advancement toward modelling and automated decision-making in subsea production system design.
Petroleum production systems consist of three integrated individual elements: subsurface reservoir, wells, and surface facility. The design, construction, and maintenance of surface facility for hydrocarbon production require simulation studies. These studies become much more realistic when well and surface facility are simulated together with the subsurface reservoir. The main objective of this thesis is to develop a framework to model the compositional multiphase/multicomponent fluid flow from reservoir, wells, and surface facility using flow tables to evaluate the pressure loss through wells and pipes. The framework is integrated to the multiphase/multicomponent compositional reservoir simulator called UTCOMPRS from the University of Texas at Austin. Two new frameworks have been developed for UTCOMPRS. The first is sequential explicit coupling and the second is sequential implicit coupling. Among three approaches for pressure drop calculation along the tubing, including the homogenous model, drift flux model, and a pre-calculated table; the main focus here is concentrated on the last method. For sequential explicit coupling, three classes of flow tables were developed and validated with a commercial simulator, which works in conjunction with the IMPEC (Implicit Pressure Explicit Composition) reservoir formulation. Also, some additional tools for controlling, and reporting the integrated models are described. Different case studies of this work demonstrated various production scenarios on the developed framework for 2D and 3D reservoirs. The accuracy of the developed framework is highly dependent on the interpolation of the bottom hole pressure and the injector constraint activation, among other operational parameters. A new tool called connection tables has been developed for sequential implicit coupling. This table processes the data, features, and map of the surface facility. With as many unknowns as the user requires, the connection table can be consistent. The mathematical explanation of the connection table is also given for each segment's condition, whether it be a flow equation or a flow table. The simulator can generate the surface facility configuration without the use of a third-party simulator once the connection table is supplied to it.As its main objective, this work presents a general framework, which analyzes the hydraulic behavior of the fluids by coupling wells and surface facilities equipment through a pre-calculated table, to provide more realistic conditions and increase the flexibility of the UTCOMPRS simulator.
Here, two new frameworks have been developed for UTCOMPRS. The first is sequential explicit coupling and the second is sequential implicit coupling. Among three approaches available for pressure drop calculation along the tubing, including the homogenous model, drift flux model, and a pre-calculated table, the main focus here is concentrated on the last method. For sequential explicit coupling, three classes of flow tables were developed and validated with a commercial simulator, which is working in conjunction with the IMPEC (Implicit Pressure Explicit Composition) reservoir formulation. Also, some additional tools for controlling, and reporting the integrated models are described. Different case studies of this work demonstrated various production scenarios on the developed framework for 2D and 3D reservoirs. Results showed that the accuracy of the developed framework intensely depends on the interpolation of the bottom hole pressure and constraint activation of the injector. For sequential implicit coupling, a new tool named connection tables has been developed. This table holds the information, details, and map of surface facilities structured. Once the connection table is fed to the simulator, it can generate the surface facility configuration without the need for any third-party simulator. The connection table can be consistent with as many unknowns as the user requires. The condition applicable to each segment, whether a flow equation or a flow table, is also explained.
