The utilization of multiple wells connected at a subsea manifold providesthe opportunity to reduce the number of risers and to reduce capital expense.The problem is the proper modeling of the reservoir well flow coupled with thecombined flow into the facility network (manifolds, flowlines and risers), which is necessary to prevent under design resulting in flow rate bottlenecksor over design resulting in extra expenditures. This paper presents a tool andmethodology for better modeling of the well to riser flow and the optimizationof riser count and configuration. Although reservoir models coupled with facility networks is not new, software enhancements provided the capability of including operation logic thatcould duplicate operations in the field. The reservoir model coupled with thefacility network provided more reasonable and accurate modeling of multiphaserates and pressures as wells were combined into a single riser. To optimize the riser count, operation logic was applied to maximize rate inthe riser at all times against the erosional velocity limit. This in turnprevented over designing by placing more risers than needed to obtain the fieldfacility capacities. The utilization of the coupled model and operation logic allowed theoptimization of the riser count for any particular reservoir model. The optimumriser count was then determined for 3 earth (geologic) models. Introduction The Agbami structure is a northwest/southeast trending four-way closureanticline, and is located on the Niger delta front approximately 65 milesoff-shore Nigeria in the Gulf of Guinea (see map in Fig. 1). Thestructure spans an area of 45,000 acres at spill point and is located in 4800ft of water. The Agbami No. 1 discovery well was drilled in late 1998. Theappraisal program was completed in 2001 and included five wells and onesidetrack drilled on the structure with each encountering oil pay. These fivewells and a sidetrack penetrated an average of approximately 350 ft of oil. One of the key outcomes of the previous phase (Phase 2) work was theselection of the facilities design. The Agbami team adopted an all-subsea, field development scheme. This scheme involved modeling all field productionand injection fluid flow through numerous subsea manifolds. One of the important objectives in the current phase (Phase 3) ofdevelopment was to determine the optimum number and locations of the productionrisers. The problem was determining how to properly model the reservoir andfacility design such that the impact of riser count can be properly quantified.The determination of this impact was necessary in order to make a qualitydecision on the riser count and configuration. Several key development decisions were determined in the previous phase(Phase 2) of the development process. These decisions were taken as givens inthis study and are listed as follows:Recommended pressure maintenance scheme and gas disposition strategy for thelower, 17 million-year (MY) reservoir is a combination of crestal gas injectionwith peripheral water injection.Recommended pressure maintenance scheme and gas disposition strategy for theupper, 14MY–16MY reservoirs is crestal gas injection only.Facility design capacity recommendations are:250,000 stock-tank bbl per day (STB/D) oil450,000 thousand cubic ft per day (Mcf/D) gas production250,000 STB/D water production450,000 STB/D liquid production450,000 STB/D water injection Reservoir Description and Uncertainty Geological Model Framework. Although the seismic quality is less than perfect, the data indicates that ahigh degree of complexity is prevalent at Agbami. The structural andstratigraphic complexity needs to be discussed briefly to set the backgroundfor the earth (geologic) and reservoir modeling.
This paper presents the results of a study of the transient performance of a horizontal well that has been completed using Inflow Control Devices (ICD's) to modify the inflow profile along the wellbore to minimize the risk of premature gas or water breakthrough into the well. A realistic pressure and rate-transient design and interpretation computational model was developed and utilized in this study. The mathematical model has been used to evaluate the transient performance of a horizontal wellbore in single and dual porosity reservoirs. The horizontal well model utilized in this paper considers the wellbore to be finite-conductivity and assumes that the well has been completed using ICD's to control the inflow rates of fluids along the wellbore. The ICD's may be installed in selectively completed intervals of the wellbore of varying lengths and number, including variation in the number and sizes of nozzles and perforations in each of the completed intervals. A wellbore outflow production systems analysis was also included in the model in order to design or evaluate the performance of a horizontal well using various lengths, grades, and weights of production tubular goods, and for varying surface operating conditions.
A tracer model utilizing scale dependent dispersion coefficient applicable to heterogeneous porous media is presented. Being a fractal model, it integrates the effects of the many length scales of heterogeneities and can be used for the prediction of fluid flow and mixing during tracer and unit mobility miscible displacements. A random field theory was used to describe the dispersion coefficient in terms of a scaling parameter~. The resulting convection-dispersion equation with the scaledependent dispersion coefficient was solved numerically by a Dual Reciprocity Boundary Element (DR-BEM) technique to generate type-curves of tracer concentration with time. This can be used in conjunction with data from field tracer tests, to determine the characteristic value of~representative of a field. A simple equation is provided to calculate the dispersion coefficient at any Icngth scale in terms of the~so determined and the field velocity correlation function. The accuracy of the model was tested by comparing its results for a range ofṽ alues representing asymptotically Fickian dispersion with analytical results and excellent agreement was obtained.
The use of multiple wells connected at a subsea manifold provides the opportunity to reduce the number of risers and capital expense. The problem is the proper modeling of the reservoir well flow coupled with the combined flow into the facility network (i.e., manifolds, flowlines, and risers), which is necessary to prevent underdesign, resulting in flow-rate bottlenecks, or overdesign, resulting in extra expenditures. This paper presents a tool and methodology for better modeling of the well-to-riser flow and the optimization of riser count and configuration.Although reservoir models coupled with facility networks is not new, software enhancements provided the capability of including operation logic that could duplicate operations in the field. The reservoir model coupled with the facility network provided more reasonable and accurate modeling of multiphase rates and pressures as wells were combined into a single riser.To optimize the riser count, operation logic was applied to maximize rate in the riser at all times against the erosional-velocity limit. This in turn prevented overdesigning by placing more risers than needed to obtain the field-facility capacities.The use of the coupled model and operation logic allowed the optimization of the riser count for any particular reservoir model. The optimum riser count was then determined for 3 earth (geologic) models. Reservoir SimulationDescription of Reservoir-Simulation Model. The Earth models were upscaled to be read by the reservoir-simulation model. The reservoir model had the xyz-grid dimensions of 72×91×260 and consisted of approximately 120,000 active cells (depending on the Earth model). The cells with a predominant shale facies were inactivated. The full-field reservoir model contained the three stacked reservoirs, as described in the Geological-Modeling Framework section.Because the fluid-property analyses indicated that the injected gas would be first-contact miscible with the reservoir oil, the reservoir was modeled as black oil with the miscible option. Fluidproperty data were obtained from three wells. An equation-of-state model was used to match the laboratory data and then to generate
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