North Arthit field in Gulf of Thailand is a gas condensate field, but also has oil reservoirs that produce from number of wells. This paper explains the implementation of in-situ gas lift and gas dump flood technologies to increase production and improve recovery from a partially depleted oil reservoir in North Arthit field. A simulation study was performed to understand reservoir characteristic, drive mechanism and expected oil rate prior to the field implementation; the study results were to allow cross flow within the tubing to dump high-pressure gas from a deeper gas reservoir into the oil reservoir to increase reservoir pressure and sweep the oil to a nearby producer. This successful pilot work has opened up the opportunities for other small oil pools in Gulf of Thailand. A proper design of the in-situ gas lift and dump flood will significantly improve the oil recovery.
This paper presents a method to approximatethe ratio of fluw rate and cumulative productionfor each resewoir in a commingledgas completion.Numekal reswvoirsimulation was used to describe flow rate and pressure response of wells completed in mutiple producing resewoirs without ,-. --.. . .. . mer-myerCrossfiow. Tine use of the method is illustratedto compare the results of simulated and field data.
This paper details out the application of a predictive analysis tool to ‘S’ Field's commingled production, aiming to enhance production allocation and reservoir understanding without the need of well intervention and a reduced frequency of zonal rate tests and data acquisition. Allocation of the production data to its respective reservoirs is performed via a novel Multi-Phase Allocation method (MPA), taking into account the water production trending evolution derived from relative permeability behavior of oil-water in each reservoir to compute flow rates for liquid phases over time. The precision of the derived rates is constrained by actual zonal rates tests through Inflow Control Valves (ICVs). This method will be cross referenced against ‘S’ Field's existing zonal rate calculation algorithm, utilizing input data from well tests results and real time pressure and temperature data. The MPA method demonstrates improvement in the allocation of production data as compared to the conventional KH-methodology as MPA takes into account the water cut trending between reservoirs. Leveraging on ICVs to obtain actual zonal rate measurements, this greatly reduces the range of uncertainty in the allocation process. MPA derived production split ratios closely match the split ratios derived from the ‘S’ Field's existing zonal rate calculation algorithm, which utilizes input data from well tests results and real time pressure and temperature data from down hole gauges. It is observed that the usage of actual measured zonal rate tests reduces the range of uncertainty of the MPA data. A combination of novel multi-phase deliverability models coupled with smart field technologies such as intelligent completions and real-time surveillance and analysis tools will increase the accuracy of the back allocation of multi-phase production data in commingled reservoirs.
Waterflood is well-known as the cost effective secondary recovery mechanism to improve oil recovery. With current challenging oil price environment, waterflood continues to be one of the main candidate of choice. Hence, it is very important to maximize by optimizing the process. The objective of this paper is to propose a rapid technique to evaluate and optimize current matured waterflooding project in an offshore brown field with complex stacked reservoirs and production system through dynamic data analyses. Interwell connectivity evaluation can assist in reservoir characterization, well placement, and evaluate waterflooding performance. Therefore, dynamic data analytics workflow applying interwell connectivity evaluation and Streamline as implicit approach are proposed. The importance of clustering each area become important to raise particular issues such as poor properties and connectivity. The production and injection points are evaluated and unswept area can be identified. Therefore, waterflood can be optimized. This study resulted if current waterflooding can be optimized and new potential well placement can be identified to increase oil recovery. Compared with no further action case, oil recovery can be potentially improved 3-4% based on numerical full-field modelling prediction. The technique will be very useful to have business decision rapidly in weeks. With current oil price situation, it can be as a cost-effective technique, especially for brown fields with mature waterflood projects and have complexity in geological and production system that commonly time consumption. The proposed workflow can be deployed to other neighbor mature fields.
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