Formation sand production is a major concern in brown field operations, especially as the field depletes and water production commences. There are many methods to control sand production in primary well completion; however, it becomes more challenging in producers where no primary sand control is installed initially, and it starts producing sand later in the well life. Selecting the right method for remediating these wells has become a hot topic with both Operators and Service Providers alike striving to discover effective and economical solutions for their brown-field operations. Currently, the solutions for through-tubing sand control in existing producers are screen hang-offs, through-tubing gravel packing1 (TTGP) and chemical sand consolidation. Through-tubing sand screen (TTSS) hang-offs above the producing zone, is an inexpensive sand control method. Unfortunately, these installations are typically short lived, often requiring regular well interventions due to screen plugging or erosion, or sand clean-out operations to remove sand accumulated in the production tubing. Alternatively, TTGP is a robust method to control sand production; however, more equipment is required to deploy the gravel pack which subsequently increases costs significantly in offshore applications. To simplify TTGP and make it economical, a major Interventions Service Provider devised a methodology to install TTGPs utilizing Slickine that reduces the overall installation cost tremendously. The methodology has been proven a great success in the US Gulf of Mexico where over 1,200 applications have been installed. The pilot implementation of slickline deployed through-tubing gravel pack (SL-TTGP) was executed in three S-Field wells in late 2018 which were shut-in due to higher than permissible sand production. These were challenging intervals in that they were uphole recompletions between cement packers in dual string 9-5/8" casing which had produced sand. The results from the installation proved that the methodology provides effective sand control and enables reinstatement of production from these wells. Further, the installations were achieved with lesser resources and at lower costs; less than half that of a CTU deployed TTGP. This success has led to further installations in the following year. This paper presents in detail the case study of the pilot implementation of SL-TTGP, key successes, as well as critical lessons learnt during execution and production phase. It includes the challenges, risks and their recommended mitigation plans, as well as the well performance comparison before and after the implementation both in terms of production and sand count.
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.
‘S’ field is a mature oilfield located offshore Sabah, Malaysia. As part of the redevelopment plan, ‘S’ field was the first field selected for an end-to-end asset management Integrated Operations (IO project) where multiple workflows have been implemented for the asset operation optimization through monitoring and surveillance. One of the exclusive workflow that will be further elaborated in this paper is on Candidate Selection and Reservoir Optimization. Although field optimization mission was ongoing, proper knowledge capture and standardization of such techniques were not adequate due to the limited data management. Lack of decision-support mechanism and most importantly the challenge was of understanding and analysing the asset performance. A key to the success of field and reservoir optimization is defining a tailored approach, for selection of right candidate and collaborative decision for well/field intervention. With an objective of full field revitalization, the project was focused on integrated, collaborative 3R approach – Reliability, Reusability and Repeatability. Reliability component was based on capturing knowledge from experienced professionals from various domains and blending that with traditionally proven analytical techniques. Reusability was emphasized by the development of consistent and robust analysis workflows ready to use. Repeatability was aiming at standardizing the process of candidate selection and decision making to assist junior engineers.
Lack of long-term production data is one of the major challenges when performing analysis for tight gas reservoirs during appraisal phase. For low-permeability liquid-rich gas and gas condensate reservoirs, fracture performance will be severely affected by condensate banking as soon as dew point pressure is reached in the vicinity of the wellbore. This makes the evaluation of fracture effectiveness and potential connected volume more challenging. Although numerical simulation can account for complex PVT, reservoir and fracture characteristics and by far the most rigorous method for forecasting, it cannot be applied to all wells due to lack of analysis time and supporting data. Therefore, a more robust methodology is required to analyze production data for a limited test period during the development phase. This paper entails an efficient and robust methodology that was applied to over 80 wells in less than a few weeks for performance evaluation, history matching and forecasting. The field in this study is a layered tight gas reservoir in the Middle East, which is currently undergoing development after an extensive appraisal plan. Most of the wells are single staged vertically fracced with their performance being significantly in comparison due to the hydraulic fracturing performance, rock quality, gas richness and operating conditions. With over 100 wells planned to be drilled in this field, it is vital to analyze the existing well performances and establish a workflow emphasizing on the near wellbore region for a robust forecasting methodology for this tight liquid-rich reservoir.
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