Gupta, Anish (PETRONAS) | Narayanan, Puveneshwari (PETRONAS) | Trjangganung, Kukuh (PETRONAS) | Mohd Jeffry, Suzanna Juyanty (PETRONAS) | Tan, Boon Choon (PETRONAS) | Awang, M Rais Saufuan (PETRONAS) | Badawy, Khaled (PETRONAS) | Yip, Pui Mun (PETRONAS)
A matrix stimulation candidate screening workflow was developed with the objective to reduce the time and effort in identifying under-performing wells. The workflow was initially tested manually for few fields followed by inclusion in Integrated Operation for an automated screening of wells with suspected formation damage. Analysis done in three fields for stimulation candidate selection will be displayed with actual statistics.
The main aim of the work was to digitalize the selection of non-performing candidates rather than manually looking into performance of each well. A concept of Formation Damage Indicator (FDI) was combined with Heterogeneity Index (HI) of the formations to screen out the candidates. Separate database sets of Reservoir engineering, Petrophysicist and Production was integrated with suitable programming algorithms to come up with first set of screened wells evaluating well production performances, FDI and HI trends up to over the last 30 years. The shortlisted candidates were further screened on the basis of practical approach such as gas lift optimization, production trending, OWC-GOC contacts, well integrity and well history to come up with second round of screened candidates. The final candidates were analyzed further using nodal analysis models for skin evaluation and expected gain to come up with type of formation damage and expected remedial solution.
For fields A and D with a total of 210 strings each, the initial FDI and HI screening resulted in 70 and 120 strings being shortlisted, respectively. This was followed by a second round of screening with 25 and 35 strings being further shortlisted as stimulation candidates, respectively. Nodal analysis models indicated presence of high skin in 90% of the selected wells indicating a very good efficiency and function-test of the workflow. In addition to selection of the candidates, the identification of formation damage type was compiled on an asset-wise basis rather than field basis which helped in more efficient planning of remedial treatments using a multiple well campaign approach to optimize huge amount of cost. The entire screening process was done in one month which was earlier a herculean task of almost one year and much more man-hours. With effective manual testing of the workflow in two major fields, workflow was included in Integrated Operations for future automation to conduct the same task in minutes rather than months.
With this digitalized unique workflow, the selection of under-performing wells due to formation damage is now a one click exercise and a dynamic data. This workflow can be easily operated by any engineer to increase their operational efficiency for flow assurance issues saving tons of cost and time.
Anuar, Wan Mohamad Anas Wan Khairul (PETRONAS Carigali Sdn. Bhd.) | Badawy, Khaled (PETRONAS Carigali Sdn. Bhd.) | Bakar, Khairul Azhar Abu (PETRONAS Carigali Sdn. Bhd.) | Aznam, Mohd Razik Mohd (PETRONAS Carigali Sdn. Bhd.) | Salahuddin, Siti Nur Khatiejah (PETRONAS Carigali Sdn. Bhd.) | Mail, Morris (PETRONAS Carigali Sdn. Bhd.) | Bakar, Afdzal Hizamal Abu (PETRONAS Carigali Sdn. Bhd.) | Trivedi, Rajesh (Schlumberger) | Tri, Nghia Vo (Schlumberger)
Gas Lift Optimization solutions have improved significantly over the past decades with the introduction of Integrated Operation (IO) in the Oil and Gas industry.
Big fields that consist of hundreds of strings, gas lift injection system, water/gas injection system and complex surface facilities (compressors, pumps, choke and valve, etc.) could establish numerous cases from different scenarios to identify production bottlenecks via simulated network models.
Using available tools, the user could model the full production system including well, surface network, reservoir, gas/water injection models, gas lift injection networks and process plants to identify bottlenecks and opportunities for optimization. The model is updated continuously using live data feed and automated technical workflow to establish an end to end solution in providing various optimization scenarios e.g. Gas Lift Optimization.
This paper discusses how the methodology works and reviews the results of gas lift optimization from four platforms consisting of over 200 strings of which 95% are gas lifted, operated using a new approach that includes live link to field data, integrated model management, and automated technical workflows to identify potential strings and gas lift supply facilities for production enhancement. This paper reviews the setup required to ensure all the necessary inputs are aligned to publish the desired outcome.
The approach has resulted in prevention of 480bopd potential deferment at platform level that can be further improved with future field implementation. In addition to gas lift optimization, the workflows have potential to expand to other business needs such as defining an accurate gas demand requirement, determining daily liquid or sand production limitation identifying underperforming wells, optimizing choke configuration, studying the feasibility of low pressure system, water treatment system, and condensate recovery system.
This paper should be of interest to those who are planning to implement Integrated Operations to their field with the aim in maximizing its value. It will provide information on the requirements, challenges, ways to overcome, and effective approach during the implementation.