The objective of this paper is to show the integrated subsurface reservoir models created for high challengeable HPHT North Kuwait Jurassic (NKJ) Gas Asset. The successful story focuses on the study and modelling achievements that involved applying the appropriate method of upscaling the fine grid static model, calibrating & initializing, history matching with field observation data and finally performing a long-term production forecast. The IPSM (Integrated Production System Modelling) tool has been used to integrate all (six) fields to fill planned facilities and optimize each field forecast to get facilities production target The new history matched models and base forecast scenarios built by an integrated multi-disciplinary subsurface team of Schlumberger, Shell and KOC staff members. KOC is the focal point and the owner of these models and the asset. The new Middle Marrat static model is supported as a tool for dynamic simulation, volumetric calculation and other static model applications. Overall the model presents a number of significant improvements over previous models such as the following list of updates: Updated non-horizontal tilted hydrocarbon contact. Refined zonation and layering to capture vertical heterogeneities observed on porosity / permeability logs Modify the log upscaling method for porosity by removing the bias by facies Update the porosity using the kriging method constrained to IPSOM Correct the log upscaling method for water saturation by using the bulk volume of water Include recent well data Updated fault distribution Discrete fracture network (DFN) model was built for Middle Marrat reservoirs. The ultimate objective of the fracture modelling work is to provide full field heterogeneous fracture properties to be used in the dynamic simulation as input for history matching and forecasting. The full field DFN which has been calibrated by PTA database. The models were upscaled and initialized with different approaches such as up-gridding method (SLB workflow) and Reduce ++ application (Shell workflow) on a field by field bases. After the history match and individual development well number and location optimization by reservoir/field, the models were coupled with IPSM tool to predict the production potential of the assets at the per field and reservoir level This tool is the key enabler for asset development planning in order to achieve KOC's gas production target of 1 Bscf/d. The integrated development planning tool allows KOC to determine the number of wells and drilling rigs required to achieve this target. As there are new coming facilities for NJK fields. The integrated development tool was also used to test the gas production plateau length after start-up of the new production facilities and the gas supply of the underlying fields/reservoirs and wells.
The first integrated development study of a green offshore field in Angola comprising of two adjacent marginal oil reservoirs is evaluated as single entity and enables decisions to be made with a view of the bigger picture. The field under consideration comprises of two small reservoirs (Reservoir 1 and Reservoir 2) located in deep-water offshore, 85 Km off the coast of Angola and operated by Sonangol P&P (the Angolan National Oil Company). The main challenge was to devise development strategies for these small reservoirs and produce them into common facilities from a nearby marginal field without jeopardizing current production profiles. Traditionally evaluation of oil and gas FDPs involves several teams evaluating various numerous independent simulation results of models representing sections of the entire system. Reservoir and network simulations would normally be executed separately and this separate analysis could result in biased development decisions being taken; and often lead to over or under designed production and process facility systems. At a time of increasing demand for oil and gas, Sonangol is also working to squeeze assets for maximum, efficient recovery and optimum production while reducing operating and investment costs. Integrated asset modelling has helped to achieve these objectives. Integrated asset modelling, couples the reservoir, surface gathering network and process facility models allowing the field-wide modelling and simulation of proposed technical developments and enhancement solutions to be evaluated as one complete system. Furthermore an economic model can also be included to evaluate the monetary impact of the solution for the entire asset. Work-overs and other remedial solutions can also be evaluated prior to taking decisions for implementation. With the use of this technology during the FDP evaluation, relatively fast analysis was performed on the entire asset, coupling these two sub-surface reservoir models to a new proposed surface gathering network model which finally links to an existing FPSO. This paper presents processes and workflows applied in the asset modelling of this green field in order to arrive at optimized, fit for purpose and cost effective FDP. The work presented here covers the construction of the well models, surface gathering network; quality control checks of two subsurface reservoir models; simulation and analysis of the results of the integrated asset model. The challenges encountered in studying this green field as an entire system, range from ascertaining reservoir global and well constraints through to network optimum sizing of down hole equipment, back pressure effects, de-bottlenecking and gas lift considerations with some insight into slugging at the riser base. Results and analysis used in the decision making process are also presented. Finally, a discussion on the impact this technology made to the entire FDP process is highlighted. Introduction With an integrated asset model, one is able to model and simulate the reservoir, gathering/production network and facilities in a collaborative manner - following fluid flow from subsurface to surface i.e. each model positioned so that the output of one model is the input to the next. Such a setup of coupled models allows asset teams to perform analysis and what-if scenarios and see the results across the entire asset.
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