Gas lift wells producing from a subsea template placed 12 km away from the processing facilities is known to be very challenging. Long pipelines give large volumes of gas and fluid which may influence each other, causing slugging or pressure variations in production pipelines and pressure fluctuations in the gas lift line. This again creates variations in rates and pressure into the process plant. Gas lift is the preferred artificial lifting method in subsea completed wells, due to the roboustness.The Yme Beta Øst subsea wells were put on production in the summer of 1996. Following a period of natural production the gas lift was started March 97. Immediately after start up of the gas lift heavy slugging in the system, both subsea and in process units was observed. As a result of the slugging the process was frequently shut down due to the pressure and rate variations. To reduce the slugging the wells were choked back, leading to reduced production. The slugging was investigated and the reason for the slugging was found to be in the production pipelines. The varying pipeline pressure influenced the gas lift system in the wells. In order to reduce this, a new gas lift design was carried out and new gas lift valves installed in one of the Yme Beta Øst wells and later both Beta Vest wells.
The objective of this paper is to highlight the necessary steps for the successful use of integrated asset modeling. It presents the full workflow for optimzing production and injection cycle times with the help of a simplified reservoir model (SRM) through the set up of an integrated asset model (IAM) to validate the SRM results and control the actual production performance. A discusson of the theory of the IAM as well as the steps to set up a SRM and IAM are presented in this paper. The steps are described in context of an actual field operation. A WAG cycle optimization workflow for the Snorre field has been created to demonstrate the advantages of using the SRM and IAM technology. The optimization process is performed using a SRM able to run a simulation run in a matter of minutes and hence being suitable for sensitivity analysis and optimization. The optimized WAG injection and production cycle is then carried forward to an IAM in order to accurately determine the well performance and the reservoir production. The IAM couples the modeling results from reservoir and well model with the surface facility network and process plant model. The coupling and integration allows investigating the impact of changes in one model to all the other models and hence also handles the proper propagation of constraints throughout the system. Introduction Coupling a full field reservoir simulation model with a surface facility network model allows for more accurate computation of hydrocarbon recovery since both system imposed constraints (fluid flow from the reservoir and surface constraints), can be considered simultaneously. The integrated asset model (IAM) comprises of a coupled system of reservoir simulation models with surface facility network models. The purpose of coupling is to balance a reservoir simulation model with the response of the surface facilities. The IAM consists of three distinct parts: The reservoir model, the well model and the surface facility model. These three models are coupled at coupling points, each passing the conditions at the coupling point on as a new boundary condition for the next model. The reservoir simulation model as a starting point computes the fluid movement and pressure distribution in the reservoir model, passing the information about the pressure and fluid saturation at the subsurface coupling point (well locations in the reservoir model) to the well models (conditions at sandface). In the well model the information about the conditions at the coupling point (sandface) is used as a boundary condition in order to compute the fluid rates or the pressure at the surface coupling point (e.g. well head), where the well model is linked to the surface facility model. The well model surface boundary condition acts as sink or source term in a surface network, which has to be balanced to account for varying fluid flow and pressure conditions in every well in the system. Their interaction will ultimativley lead to a newly calculated backpressure of the production system for every well. The system backpressure is then conveyed all the way back through the well model back into the reservoir in order to account for the changed boundary condition imposed by the surface model in the reservoir.
Summary Water injection is commonly used to improve oil recoveries in depleting reservoirs. However, insufficient injectivity can result in water-injection projects being limited in injection rates, which can sometimes make them uneconomic. Implementing water-injection projects requires a multidisciplinary approach to optimize water-injection rates for reservoir-performance, cost, and well-design considerations. The costs for the surface facilities are dependent on the required water quality, water temperature, and other operating parameters that are linked to the injectivity of water. A work flow including quantitative assessment of the injectivity development as a function of the operating parameters as well as the uncertain geomechanical and reservoir parameters can be used to improve the surface-facility design. Such a work flow was applied to a shallow offshore field. The results showed that the base-case design of the facilities should be modified to avoid an increase of the flowing bottomhole pressure (BHP) above the minimum stress of the caprock. The effect of the various parameters on the BHP was investigated, and the sensitivity of the BHP to uncertain input parameters under different operating conditions was tested. The results indicated that the BHP does not exceed the BHP limit, and hence the injectivity is expected to be high enough for a sufficiently long period of time under a wide range of conditions.
Water injection is commonly used to improve oil recoveries in depleting reservoirs. However, insufficient injectivity can result in water injection projects being limited in injection rates which can sometimes make them uneconomic. Implementing water injection projects requires a multi-disciplinary approach to optimize water injection rates for reservoir performance, costs and well design considerations.The costs for the surface facilities are dependent on the required water quality, water temperature and other operating parameters which are linked to the injectivity of water. A workflow including quantitative assessment of the injectivity development as a function of the operating parameters as well as the uncertain geomechanical and reservoir parameters can be used to improve the surface facility design.Such a workflow was applied to a shallow off-shore field. The results showed that the base case design of the facilities should be modified to avoid an increase of the flowing Bottom Hole Pressure (BHP) above the minimum stress of the caprock. The effect of the various parameters on the BHP was investigated and the sensitivity of the BHP to uncertain input parameters under different operating conditions was tested. The results indicated that the BHP does not exceed the BHP limit and hence, the injectivity is expected to be high enough for a sufficiently long period of time under a wide range of conditions.
Reservoirs in the Barents Sea are several times shallower than in other parts of the NCS, essentially due to recent uplift and erosion of younger sediments. A proper understanding of their geomechanics is considered paramount for their successful development. In turn, the lack of any available analogue makes the proper in situ measurement of key parameters compulsory. The paper describes the planning and execution of an appraisal well solely dedicated to the purpose of geomechanics data acquisition in the shallowest oil reservoir on the NCS – i.e. coring, logging, XLOT and injection testing. It focuses on the operations conducted in the oil reservoir itself, which included an entirely novel multi-cycle injection test aimed at estimating the large-scale thermal stress coefficient of the formations around the well – i.e. the impact of the injection temperature on the fracture pressure of the formations. Every operation in the well was challenging due to the sea depth being about twice that of the overburden thickness and to the formations being quite consolidated, which was met by careful iterative multidisciplinary-planning. The equipment was often taken to its limit and sometimes extended beyond its standard use – e.g. the metering systems. The injection test itself could not be performed traditionally – i.e. use of surface data and downhole memory gauge. Instead, the downhole gauge data were sampled, pumped out and transferred to a remote site where real time advanced analytics was used to ensure that safety criteria were always met throughout the operation in terms of vertical fracture propagation and lack of reservoir compartmentalisation. In addition, this allowed adjusting the planned injection schedule to the exact formation's response, which could not be fully quantified ahead of time. All the targets of the appraisal well were met. The injection test – i.e. the shallowest on the NCS and perhaps worldwide in an offshore environment – was performed successfully. Its main results are considered essential for a possible future field development – e.g. the injectivity is confirmed and, in addition, a significant thermal effect is proven. The series of novel technologies deployed in the extreme environment presented in the paper can easily and beneficially be extended to more traditional reservoirs. This concerns performing multi-cycle injection tests on appraisal wells on a systematic basis to prepare and optimise the development plan, real-time monitoring through advanced analytics and adjustment of these tests, start-up of injection wells during field development, monitoring and optimisation of water injection schemes, etc.
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