This paper elaborates on the concept of successfully applying one combined platform that includes gas condensate dynamic simulation models, surface network, and individual well models interacting and running sequentially within a closed loop. The study also highlights the value created by integrating dynamic modelling, simulation data, history matching (covering gas condensate reservoirs consisting of gas producers and injectors under the recycle mode) with continuously calibrated well and network models, thereby allowing end-users to make the best use of an integrated system for their dynamic production forecasting. The dynamic reservoir integration methodology incorporates as a first step the data coming from the reservoir simulator model as the main source of reservoir parameters to build a comprehensive system for enhancing production forecasting profiles. In an automatic routine, the simulation data provides the Inflow Performance Relationship, which gets transferred to the well's models, so a well performance curve (WPC) can be generated automatically. Once the latter is generated, it gets transferred to a recycle production-injection network model where a user-configured surface network scenario optimizes in an IAOM (Integrated Asset Operation Model) environment to calculate the rates corresponding to each well taking into consideration distinct constraints. The rates generated are transferred back to the reservoir simulator as well control parameters to initialize the next step of the loop and begin the process under updated conditions. The number of steps, termed as the schedule of the run, are determined by the user based on the forecasting objectives. From the practical point of view, this dynamic reservoir integration mainly targets at getting the best possible assessment from the available data, assumptions, and constraints. The value generated by having a dynamic integration, including all main components of the field/reservoir production, initially relies on the accurate understanding of the dynamic behavior of the hydrocarbon reservoir in order to predict future performance under different development and production approaches. There are several reasons why an integrated approach proved to have strong value creation: Reliable evaluation of the entire production system from reservoir to processing facilities. Continuous assessment of well and network performance. Verifying consistency of data reducing uncertainties. Minimizing underlying assumptions and constraints. It is worth mentioning that during this implementation, the entire system employed compositional models where a high number of components and pseudo components were part of the system, and the thermodynamic behavior added further rigor to the overall calculations. This advanced methodology of carrying out dynamic integration of surface to sub-surface in a production platform framework enhances various key factors of numerical simulation, such as run time estimation, optimal incorporation of surface parameters, identifying gaps between the surface and sub-surface system and enabling the user to perform key business scenarios in an efficient and flexible workflow-based production platform system.
There are several operational challenges associated with a gas field producing in recycle or depletion mode, including a reasonable forecast and a robust production strategy planning. The complex reservoir dynamics further demands faster and reasonable analysis and decision-making. This paper discusses an all-inclusive integrated modeling approach to devise a production strategy incorporating the detailed compressor design requirements to ensure that a consistent production-stream is available in the long-term considering technical and economic aspects. The proposed production strategy is a two-fold approach. In the first step, the process utilizes the current reservoir simulation data in the production-forecast model. This history matched model captures the reservoir dynamics such as reservoir pressure decline and accounts for future wells drilling-requirements. However, the detailed production hydraulics in wellbore and surface facilities is not captured in the model. Further, to consider the declining well-performance and facility bottlenecks, integrated analysis is required. So, in the second step, the reservoir simulation model is dynamically integrated to take the input from the production model, encompassing detailed well and surface facility digital twins. The continuous interaction provides a highly reliable production profile that can be used to produce a production strategy of compressor design for the future. A strong interactive user-interface in the digital platform enables the user to configure various what-if scenarios efficiently, considering all anticipated future events and production conditions. The major output of the process was the accurate identification of the pressure-profile at multiple surface facility locations over the course of the production. Using the business-plan, field development strategy, production-profile, and the reservoir simulation output, reliable pressure-profiles were obtained, giving an indication of the declining pressures at gathering manifold over time. A well level production-profile-forecast helped in prioritizing wells for rerouting as well as workover requirements. As an outcome of this study, several manifolds were identified that are susceptible to high-pressure decline caused by declining reservoir pressures. To capture this pressure decline, a compressor mechanism was put in place to transfer the fluid to its delivery point. As this study utilizes several timesteps for the production forecast estimation, flexible routine options are also provided to the engineers to ensure that backpressure is minimized to avoid a larger back pressure on the wells for quick gains. This solution improves the efficiency of the previous approaches that were entirely relying on the reservoir simulation model to capture the pressure decline at the wellhead to forecast the compressor needs. In this methodology, the pressure profile at each node was captured to simulate a real production scenario. This holistic approach is in line with Operator's business plan strategy to identify the needs of external energy-source to avoid production-deferral.
Forecasting oil and gas production for a well or reservoir is one of the most valuable tasks of a reservoir engineer. This paper elaborates on the assessment of production targets deliverability using a dynamic and integrated approach to perform short term production forecasting. The case also studies the seamless integration of sub-surface with well and facility network models providing options to examine the feasibility of production plans. The principal approach employed in the methodology comprises an automated workflow, which includes reservoir simulation data, wells, and network models enclosed in a dynamic loop, where workflow iteration takes place until the production target is achieved. Within this implementation, the process allows the estimation of short-term production forecasts mainly used for optimizing production operations and business planning, among other tasks. Some of the main steps followed in order to assess the feasibility of the production targets are: Well, Network and Reservoir data QA/QC and further alignmentNarrowing down of gaps between the surface and sub-surface systemIntegration among the several data-driven sourcesIteration of the overall process allowing minimal human intervention Throughout this implementation, it was clearly appreciated that production forecasting represents a highly complex task due to the number of different components included in an integrated system and their intrinsic interconnection, where essentially every piece of the calculation influences others. The case study highlighted how performing a dynamic reservoir integration run in an integrated digital production system can help engineers to provide a way to check the feasibility of short-term production targets while considering full surface system configuration. Moreover, the integrated production system provided flexibility in terms of setting up forecast scenarios in an efficient manner, thereby minimizing users' time and efforts in data handling and driving maximum user focus on results and analysis. A dedicated forecast server helped in achieving run performance, thereby enabling the user to carry out various what-if scenarios in a short amount of time. The case studies also discuss a few key challenges encountered during the process that represented a difficulty in overcoming unless addressed in an integrated collaborative system: Data size and complexityLack of data and/or data inconsistencySurface and Sub-surface model configuration for dynamic integrationGaps between surface and sub-surface performances at initial time step. The application of this integrated and automated workflow approach improved confidence in the reservoir target deliverables by providing robust data management and better predictions resulting from evaluating the entire system (including the performance of wells and reservoirs at the same time). This helped in saving user analysis time significantly by avoiding the process of analyzing all the sections of the system in isolated silos, which is usually the approach followed by many operators with large amounts of wells.
This paper addresses the opportunities of maximizing the condensate production in a giant Recycle Gas-Condensate Reservoir in UAE. The condensate reservoir is producing many years under recycling mode to maintain the pressure and maximize the gas condensate recovery. The producers and injector wells are in a line drive pattern where the injected fluid is lean gas to maintain 100% VRR. The condensate production declined through the years due to gradual pressure decrease as well as injected lean gas/N2 breakthrough. Several studies were done to increase condensate recovery and extend gas production plateau.
Revamping/optimizing production from one of the Mega gas condensate field with multistack reservoirs requires integrated solutions combined with advanced technologies and best practices. The topic shows the future major options to develop the reservoir either to sustain the current mandate or to ramp up the production from current production to avail more gas to the network due to the high demand. In addition, gas compression station was taken as part of the major future option to study the possibility of extending the gas plateaus. A detailed study of possible options considered for Mega Gas Condensate reservoir with high CGR was conducted, targeting the condensate rich peripheral area of the field. The core objective was to study the possible options in order to recover the rich components that may have migrated to the field flanks – and in doing so, maximizing condensate recovery and maintaining wet gas production plateau. It worth to mention that the strategy of developing this reservoir also targeting to avail more gas to the network due to the gas demand. All the surveillance data have been utilized and integrated in the modeling efforts and reservoir development plan. Three major scenarios were evaluated with alternative options for well location and strategies for injection and production pattern. The first scenario was peripheral injection, where peripheral injectors were drilled to maximize the reservoir pressure in the flanks in order to sweep the condensate towards existing crestal producers. The second and the third strategies were staggered and direct line drive cases, where fixed patterns of injectors and producers were drilled in the peripheral area with a dual objective of sweeping condensate and directly accessing bypassed areas. Extensive sensitivity analyses were conducted to reduce the number of wells from 91 to the final optimized number (22 wells scattered across the peripheral area). Field and well level sensitivity analyses were performed on the optimized selected scenario in order to define the optimum completion, field/well level operating production/injection conditions. This included analysis of blowdown time, production and injection rates, and injection stream composition. Moreover, the study includes several sensitives conducted to avail more gas to the network through under injection, which will associate with condensate dropout/banking issues. This issue will be addressed as part of future SCAL and R&D studies to understand the mechanism of recovering condensate dropped-out in the reservoir. Sectorization Voidage Replacement Ratio (VRR) study was conducted to improve the intake/offtake balance and further optimize the VRR to minimize and manage the impact with less gas injection due to Gas demand. This is very significant during the implementation and monitoring phase. The paper discussed about several Issues, challenges associated with the Gas Condensate Field and the integrated plan expected to be implemented in the future including drilling triple lateral (Maximize Reservoir contact), Underbalance Drilling pilot, Hydraulic-fracturing Pilot, Geomechanics stud. Etc. The complexity of such multi-stacked reservoirs including the heterogeneities in rock and fluid from one side to diverse development strategies requirement on the other side calls for integrated solutions combined with advanced technologies aiming to maximize HC recoveries.
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