Integrated Surveillance Offshore Turkmenistan
- Chris Carpenter (JPT Technology Editor)
- Document ID
- Society of Petroleum Engineers
- Journal of Petroleum Technology
- Publication Date
- March 2018
- Document Type
- Journal Paper
- 70 - 72
- 2017. Society of Petroleum Engineers
- 0 in the last 30 days
- 88 since 2007
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This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 188357, “Integrated Surveillance in Cheleken Block Offshore Turkmenistan by Use of Automated Steady-State and Transient Models,” by Roberto Espinoza, Dragon Oil, and Suraj Mohan Uniyal and Ivan Marcelo Jaramillo Rivadeneira, Schlumberger, prepared for the 2017 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, 13–16 November. The paper has not been peer reviewed.
The complete paper describes a work flow in which wells and production networks (15 platforms and 100 active wells located in the Cheleken Block offshore Turkmenistan) are automatically modeled daily with steady-state and transient tools and ultimately analyzed by a Web-based surveillance system, the Cheleken Block Central Data Gathering System (CDGS). These models are updated and run automatically on a daily basis by means of the CDGS.
Well and network modeling are being used widely across the industry as a method of problem detection, production enhancement, and production optimization. However, well and network modeling require a large amount of data that needs to be systematically collected, cleaned, validated, and updated. They also require considerable manpower, because many time models are not calibrated adequately to ensure reliable results.
An operator has implemented a robust system, the CDGS, that allows data capture, validation, and approval in a systemic manner. There was a need to capitalize on this ability and integrate it with steady-state and transient models to increase the efficiency of the overall process.
The initial status of the project presented several critical challenges:
- Well models were executing sporadically.
- The network model did not consider the frequent well and network flow routing.
- Optimization of choke or flow routing was not possible with the current configuration.
- Visualization of day-to-day flow routing and other production key performance indicators of the field in a centralized system was required in order for the operators, supervisors, and reservoir teams to reduce their nonproductive time, solve day-to-day operational problems, and optimize field production.
The project was designed and implemented on the basis of four fundamental processes.
- A production-data-management system (PDMS) was implemented to systematically acquire all well-operation data and process information generated during day-to-day activity from producing assets. These data needed to be validated, stored, and made available in a structured manner to different user groups. Various core-analytics processes such as back allocation, virtual flowmetering, volume correction, and software-platform integration were performed to automate data flow.
- A single, integrated platform for monitoring and surveillance of operational parameters across the entire field was implemented. This integrated surveillance tool provides a single platform that connects operations for a broad range of disciplines.
- Software from different vendors that performed steady- and transient-state well and network analysis and diagnostics was integrated to the core PDMS. The models can be run on a daily basis, and their results can be stored in the system to be visualized.
- Day-to-day optimization for choke and flow routing of the production network can be performed with these steady-state and transient models, with results provided to the operators to implement in the field.
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