Case Studies

Context

• Offshore field with wells which produce to an FPSO through sub-sea tie back lines.
• Wells producing oil, condensate and dry gas.
• Test separator installed, however individual testing of wells challenging due to flow assurance issues.
• Multiphase flow meters on the manifolds for well testing.
• Voidage maintained through gas injection.

Objectives

• Consistent PVT Handling.
• Well Allocation and Surveillance.
• Standardise  well test process and reporting.
• Flow Assurance monitoring and surveillance (Wax, Hydrates, Flow Induced Vibration and Erosion).
• Reservoir surveillance (Reservoir Pressure and Voidage Monitoring).
• Optimisation.
• File management .

Approach taken

• Engineering Workshop to understand and review the data and to build valid models.
• Define the processes (workflows) that will be needed to address the challenges.
• Capture the processes within the DOF platform and configure a system so that engineers can make informed decisions about the field.

  All of this was achieved in a few months.

Value delivered through implemented solution

• Digital Oil Field Solution implemented.
• The system delivers reliable physics-based allocation which enables engineers to perform surveillance on the reservoir, wells and network.  This leads to more informed decisions.
• The system provides optimisation guidelines to increase production.
• The system delivers a common platform that brings different disciplines together.

Context

• Large onshore oil field with a combination of ESP, GL, naturally flowing and water injection wells.
• Wells flowing to multiple different separators through a complex network system.
• Extensive well routings provide both optimisation opportunities as well as challenges, affecting aspects such as:
  • Production Allocation
  • Ability to QC models
  • Ability to understand the effect of any decisions taken in the field.
• Wells and Field subject to many physical and operational constraints.
  • ESP up-thrust and down-thrust limits
  • Maximum gas in ESP / Minimum Pump intake pressure
  • Flow assurance limits in network
  • Separator capacities
  • Reservoir Management strategy / constraints

Objectives

• Increase production
• Maximise reserves
• Reduce operating costs

Value delivered through implemented solution

• Integrated model of field built.
• Digital Oil Field System implemented.
• The system is being used to generate recommendations to the field physical, operational and strategical constraints.
• Increased of production achieved (without capital investment).
• Better understanding.
• The understanding gained through the creation and validation of the network model contributes to a better production allocation, improving reservoir models and hence improving forecasting and planning.
• The model provides a robust basis for decision making and drives improvements which otherwise would not be looked at.
• Collaboration and communication.
• The system integrates multiple departments/divisions within the company, all contributing towards the bottom-line.

Context

• Green field offshore gas condensate field.
• HPHT in challenging environmental conditions.
• High rate condensate wells.
• Platform wells with offshore processing facilities.
• Gas exported via long pipeline to join gas distribution system.

Value delivered through implemented solution

• Delivery of a rigorous model based Digital Oil Field System.
• Rigorous technical allocation that provides detailed understanding of the field.
• Rationalising the well test process.
• Process virtual meter rates and water vapour used for allocation, well testing and scale.
• Detection of chemical scale issues and mitigation.
• Constant recommendations to increase production.
• Putting the system in place before field start allowed updates to field development & operational plan and increased understanding of field.
• Knowledge sharing enabling ownership of the system to be with the client.

Context

• Offshore Gas Condensate Wells.
• Multiple platforms.
• Production from various platforms connects to shore via three dedicated long multiphase pipelines.
• Production feeds multiple Slug Catchers which in turn feed LNG trains.

Field Management

• Field production controlled (constrained) by a gas demand (gas contract), which changes periodically.
• Significant field spare capacity and hence multiple field operating solutions available to meet demand.
• Preferred operating solution is governed by a combination of Liquid (Condensate) production optimisation and reservoir management strategy (to maximise reserves).
• This is captured in well production targets generated by the Production Optimisation team which Operations use as production guidelines.

Technical Challenges

• Many wells show rate-dependant Gas Oil Ratio behaviour mainly related to a varying contribution of different layers (affecting the produced fluid composition).
• This has significant effect on the optimisation of liquids (condensate), for the wells’ “GOR ranking” become rate dependant. This also impacts flow assurance.
• Long multiphase pipelines with their associated flow assurance implications.
• Field Measurements highly dependent on conditions of P&T.

Operational Challenges

• Field subject to many planned and unplanned events which operations need to react swiftly to keep meeting gas demand.
• Lack of information makes difficult to quickly assess the impact of field operations decisions on reservoir management strategy, production optimisation and flow assurance aspects.
• At least five different groups directly involved in the generation of guidelines or key supporting activities.

Solution

• Engineering Models
• Model Validation / Update processes
• Real Time Field and Well Surveillance
  • Production: current and target
  • Operational KPIs
  • Reservoir/Production Management KPIs
• Optimisation
  • Reacting to Operational changes
  • Prepare for anticipated changes
  • Monthly guidelines

Value delivered

• The DOF system introduces rigorous physics to a complex optimisation problem.
• Provide the integration required between processes and people needed to support effective implementation of the recommendations.
• Achieves long term deliverability and secured contractual LNG demands by meeting targets and honouring constraints.
• Improves the process of developing production guidelines.
• Rigorous daily well management to ensure that the wells are being operated within the guidelines set by reservoir management with an ‘automatic alarm’ functionality to indicate any deviations.
• Different scenarios to be studied when maximising long term field recovery along with meeting the short term objectives of maximising the condensate recovery, minimising H2S content in the produced gas, controlling the salinity in the pipelines, etc.
• Flexibility to respond to unexpected short term scenarios.
• Engineers can make prompt and effective decisions regarding well rate adjustments in the event of unexpected upsets, constraints or sudden increases in demand.
• Creating production schedules to predict any planned or intervention activities such as pigging operations, train turn around, platform shut-ins, etc.

Context

• Offshore, gas-lifted field
• Dual-gas lift
• Surveillance, Allocation and Optimisation Challenges

Solution

• Advanced surveillance workflows
• Dynamic operating Envelope with all constraints
• Dual Gas Lift diagnostic, Optimization and allocation 
• Sand Management for the entire asset
• Flow Assurance

Context 

• Large onshore oil field
• Naturally Flowing and ESP wells
• Water injection (water flood) to maximise recovery

Objectives

• Primary Objectives
  • Reservoir Management and Optimisation
  • Maximise reserves (recovery)
  • Optimise production (within above long term strategy)
• Secondary Objectives
  • Field Surveillance and Monitoring

Challenges

• The optimisation of recovery requires understanding the dynamic processes inside the reservoir and the ability to assess the impact of actions taken today will have in 10, 20 years’ time.
• This requires the appropriate reservoir model to be part of an Integrated Production Model (IPM).
• Processes that continually validate the wells and network are well established.  However, the validity of the reservoir models are assessed less frequently.
• In practice this involves incorporating many different processes, data and disciplines to do successfully.

Solution

• Rigorous procedure for validating different reservoir realisations/models.
• The integration of a valid numerical reservoir simulation model allows us to incorporate activities including:
  • Water Injection allocation
  • Water flood management optimisation
  • Voidage replacement monitoring
  • Water breakthrough time prediction
  • Short/Medium/Long term Forecasting

Context

• Large well count
• Onshore shale
• Large acreage

Objectives

• Optimize and maximize field recovery
• Higher operational efficiency
• Increase revenue

Solution

• Digital Oil Field Solution implemented.
• Engineering and exception-based data driven workflows created to increase visibility to production enhancing opportunities and value.
• Integration of  physics-based and data driven workflows.
• Automation to further integrate and streamline the digital process.

Context

• Deep Water.
• Multiple subsea templates, risers & separators.
• Gas Lifted production supported by gas injection.

Objectives

• Engineering Objectives:
  • Production Optimisation.
  • Production Monitoring and Surveillance (incl. Allocation).
• Technical Challenges:
  • Uncertainty on wells’ Gas Lift gas injection (allocation).
  • Limited Real Time Measurements (e.g. ~50% of WHP and/or FLP missing).
  • Inability to test wells in isolation (due to stability on riser). Wells are normally tested comingled and hence the production test analysis presents a production allocation challenge in itself.

Solution

• Data Limitations and uncertainties
  • Reduce uncertainties (e.g. Gas Lift injected) as ‘upstream’ as possible from the field management processes (hence avoid propagating these through).
  • When possible, use models to fill data gaps with ‘best estimates’ to avoid having to deal with them on an ad-hoc basis on every process.
• Continuous field surveillance and monitoring
  • Exploiting any redundancy of data to further reduce uncertainties and continuously improve our representation of the field (Model).
• Optimisation
  • Integrate all the above to ensure optimisation activities are carried out with good quality and valid models.

Implementation Steps

• Engineering workshops.
• Build, validate and calibrate physical models.
  • PVT study (PVTP)
  • Well Models (PROSPER)
  • Surface Network (GAP)
  • Reservoir Model (MBAL, Reveal, Eclipse, etc.)
  • Other Models as required (e.g. Process)
• Test workflows / methodologies off-line (RESOLVE).
• Validate approach, workflows and methodologies using historical data (vs time).
• Deploy solution within real time system.

Solution Delivered

• A fully integrated, scalable, upgradable off-the-shelf platform to meet the engineering objectives.
• Addresses the uncertainties and missing data in a rational and integrated way.
• Better quality models.
• Generate rigorous optimisation calculations.