Integrated Surveillance Offshore Turkmenistan

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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.

Philosophy Applied

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.

PDMS and Infrastructure Description

Installing the Production Platform. To provide synchronization, overcome any connectivity limitations, and allow platform operators to have access to the production platform with a minimal effect on delay, latency, or computer infrastructure, click-once technology was implemented. This enables the user to install and run a Windows-based smart client application by clicking a link in a Web page.

Integrated Steady-State Work Flow. Updating Well Parameters With Steady-State Models. The PDMS is defined to hold all steady-state well models by which the operating parameters will be updated automatically and systematically. Data validation is essential for ensuring that before the application computes data or provides data to the well models, the information collected is verified to be clean and correct. The application uses routines that check for the correctness and meaningfulness of the data entered into the system. The system includes tools and procedures to integrate data among different software platforms, including a work-flow builder capable of interacting with the selected well-modeling tool (e.g., steady-state nodal analysis).

The work flow passes key validated data (parameters) from the PDMS to the well-modeling tool. These parameters include wellhead pressure (WHP), wellhead temperature (WHT), choke size taken from routine wellhead recordings, water cut (WC) from routine well samples, and gas/oil ratio (GOR) available from the latest well tests on which pressure/volume/temperature corrections have been previously applied.

Inflow-Performance-­Relationship (IPR) and Vertical-Lift-Curves (VLC) Work Flow. Once well models are uploaded and the required data are available in the PDMS, the well-model-update work flow can be run automatically or on demand, which would update the following parameters:

  • WHP, GOR, and WC in system analysis
  • WHT in the geothermal gradient against the first depth mentioned

After updating, the work flow runs the system analysis and saves the estimated bottomhole pressure in the wellhead data screen. The well model is then updated in the PDMS. The lift curves are generated once a month automatically or on demand, to be used in the network model.

Network Solver Work Flow. Well-Flow-Routing Status. One of the significant innovations of the project is the acquisition and updating process of the well-flow-routing status. Flow-routing status considers a complete work flow to allow the PDMS system to record where a well is being routed.

  • Flow routing on wells includes flow diversion to the different existing manifolds or direct diversion to risers and production lines.
  • Flow routing on manifolds includes flow to production and testing separators or direct diversion to risers and production lines.
  • Flow routing on separators includes independent flow routing from each separator outlet.

When the wellhead parameters are passed automatically to the modeling tool, routing status of wells and separators is also automatically passed to the network-modeling tool along with choke settings.

Network Simulation Work Flow. This work flow imports IPR data from respective well models, generates VLCs, updates the choke size for each well, and updates separator pressures before running the network model. After the run, it saves estimated rates and pressures for wells, pipelines, manifolds, and risers.

Rates Estimation: Flow Through Chokes. A secondary process of empirical well-rate estimation is performed on the PDMS. This method, along with well-test measurements, defines a base in order to determine whether the results of the model’s area present an acceptable range of deviation or whether wells and network models need to be calibrated manually.

Integrated Transient Work Flow. The transient or dynamic multiphase-flow simulator models time-dependent behaviors, or transient flow, to maximize production potential. Transient modeling is essential in the field-development and production phases of oil and gas assets and is used to design production systems and determine the best operational strategies. Dynamic simulation is used extensively to investigate transient behavior in pipelines.

After steady-state models are run, the integrated transient work flow used in this project passes parameters from the PDMS to the platform to the transient model. These parameters include total calculated rates and GOR and WC at each riser, along with the measured pressures and temperatures. Once the parameters are updated, the transient model is run automatically to solve pressure and rate fluctuations along the production network.

Integrated Surveillance. A centralized, Web-based integrated surveillance tool representing the field network was developed in addition to the CDGS to visualize and analyze various data recorded and modeled within the field network in an intuitive manner. The frequent routing of wells in the field posed a challenge, so automated mapping and visualization of these routings in the CDGS was implemented. The routing is automatically updated in the steady-state field network, keeping the model up to date, properly configuring the production data for feeding into the transient model, and updating the Web-based integrated surveillance tool with proper flowline color coding to represent true field production flow on a real-time basis.

A customized, integrated surveillance tool provides a state-of-the-art platform to visualize the data in an intuitive manner—simplifying the navigation from an overall-asset-production, platform-level, and well-level view—and offers tool tips showing various rates and the actual and estimated pressures in different elements of the field view.


  • With the implementation of this work flow, all manual processes related to data loading and model update were automated. The time used on these tasks was reduced dramatically, from days to hours.
  • After implementation of the work flow, the routing configuration can be monitored on a daily basis to compare the resulting production with the model. This way, different what-if configurations can be modeled and can be compared with actual results to maximize field production.
  • The daily update of the models and the comparison of modeled rates with actual rates allowed engineers to control the quality of the models, increasing significantly the reliability of the entire surface-model system.
  • Having different models and prediction results at hand allows surveillance engineers to manage all events by exception and by priority. This way, problem wells and bottlenecks are easily predicted, detected, and managed.
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.

Integrated Surveillance Offshore Turkmenistan

01 March 2018

Volume: 70 | Issue: 3


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