IN THE LATE 2000s, Kuwait Oil Company (KOC) launched a
programme to bring digitalisation to the hydrocarbon producing
fields in the North Kuwait (NK) asset. It started with a pilot project
covering 49 wells (out of 1,200+ onshore wells in NK) to assess the
value of digital technologies. Over the next decade, the programme,
named KwiDF (Kuwait Integrated Digital Field), would grow into one of
the leading digital oilfield implementations in the Exploration and
Production (E&P) industry, both in terms of its scale and ambition. With
the recent announcement of Phase 2, representing the expansion of
Phase 1, KwiDF is set to leapfrog the digitalisation efforts across all
KOC’s producing assets in Kuwait. As KOC’s technology partner,
Halliburton will support this expansion, leveraging the
DecisionSpace® 365 platform.
Business drivers for KwiDF
More than 70% of production globally comes from mature fields today
– some of them producing for several decades. With age come
operational challenges such as reservoir productivity decline, well
integrity and flow assurance issues, equipment malfunction and
unstable well behaviour.
"The labour-intensive mode of
operations reduced visibility of the
operating conditions in the field and
delayed the response to anomalies"
Fields in NK, several decades into production, had started to show
signs of the same late-life challenges, including declining reservoir
pressure, increasing water cut and frequent trips/failures of surface and
downhole equipment, to name a few. Further amplifying these issues
was the prevailing operating model in NK. Day-to-day production
monitoring relied on the field technicians travelling to the remote well
sites for data gathering. The asset specialist teams in the office waited
for the data to come from the field so that they could do performance
analysis, which itself would be a time-consuming effort given the
sporadic data and lack of the right tools.
The labour-intensive mode of operations reduced visibility of the
operating conditions in the fields and significantly delayed the response
to anomalies, which often festered unnoticed until they caused
production downtime. Costs went up too due to frequent well
intervention activities needed to keep up the production.
KwiDF Phase 1 – delivering the foundation for growth
KwiDF sought to be an answer to these issues, with specific goals to
improve well performance, unlock workforce productivity and reduce
cost. The initiative was set in motion with KOC selecting Halliburton to
implement a pilot project targeting the following digital capabilities:
- Outfitting 49 wells from NK Sabriyah field with wireless sensors and
setting up appropriate technology infrastructure to bring real time
data from the well sites to office
- Integration with existing KOC data sources and models including
third party data sources (real time historian, production, completion
and corporate), third party well and network modelling tools and in-house data sources
- Smart alarms for exception-based surveillance
- Work process automation to speed up engineering tasks (e.g.
performance analysis, diagnostics, model calibration)
- Dashboards to deliver context-specific data visualisation to KOC users.
Nine well and reservoir management workflows were targeted for
digitalisation, of which the ESP (Electrical Submersible Pump)
surveillance and optimisation workflow became one of KwiDF’s most
important, given over 70% of the NK wells are producing with ESPs.
The workflow delivered exception summaries, smart alarms, detailed
well information, diagnostic tools and an optimisation engine. The latter
allowed users to rapidly evaluate various opportunities for production
gain such as changes in pump frequency or well head pressure, thus
saving time for the KOC users who would manually perform those
The pilot demonstrated tangible benefits in terms of productivity
increase and faster decision cycles. This encouraged expansion to 140
wells followed by a full-scale roll out of the entire solution covering
nearly 1,200 wells and five gathering centres in NK, culminating in full
operationalisation of Phase 1 in 2018. As part of that, a state-of-the-art
collaboration centre was also constructed to facilitate inter-disciplinary
collaboration and streamline communication between the field-based
operations team and office-based technical specialists.
Phase 1 yielded a 4-5% production increase as observed by KOC,
resulting from early detection of anomalies and faster response to
them. Staff productivity multiplied due to work process automation,
which minimised human efforts on low-value repetitive tasks such as
data gathering, filtering, model update and production reporting.
"Phase 1 yielded a 4-5% production
increase as observed by KOC. ”
KwiDF Phase 2 – expanding and sustaining value
Phase 2 expands the KwiDF scope to target value creation in new
areas such as reservoir management, production optimisation and
operational efficiency improvement. Expansion identifies the following
four key initiatives that will be deployed on top of the DecisionSpace
365 platform. The platform will leverage existing functionalities of Phase
1, but also deliver more advanced capabilities in the form of digital
twins incorporating machine learning models and data from advanced
subsurface sensors and IoT devices on wellheads and the pipeline
1. Intelligent reservoir management (IRM)
IRM will advance understanding of the NK reservoirs to enable field
development planning and waterflood surveillance and optimisation. A
full field digital twin integrating subsurface and surface performance
models will be developed to aid evaluation of field development
scenarios, including adjustments to waterflooding strategy. Near
wellbore sensors will be deployed to measure field resistivity and
achieve superior reservoir characterisation.
2. Well productivity and uptime optimisation (WPUO)
This initiative will augment the well performance management solution
delivered in Phase 1. New digital capabilities such as predictive
analytics developed using machine learning techniques will assist in
early identification of abnormal well conditions and definition of optimal
remedial action, thus maximising well uptime and productivity.
3. Integrated production optimisation (IPO)
Over the years, the complexity of NK operations has seen a steady
rise. Asset teams are challenged to meet the production targets against
dynamic flow bottlenecks in the production network and unplanned
remedial or safety critical activities, rendering parts of the production
The digital enablement of IPO will centre on a digital twin, underpinned by automated work processes and data visualisation,
offering an integrated representation of wells, pipeline network and
surface facilities. It will assist in running NK producing assets to their full
potential through identification of optimal network routings and operating
set points. It will also aid decision making on actions to mitigate
unexpected production shortfalls caused by operational upsets.
4. Pipeline monitoring (PMON)
PMON will focus on maintaining productivity and integrity of in-field
pipeline network by enhancing data and analytical capabilities.
Additional sensors will be installed to allow continuous measurements
of flow condition and assure the quality of the network model
incorporated in the IPO digital twin.
The digital twins mentioned above, through on-demand simulation
of the NK production system and its constituents (reservoir, well,
pipeline network and facilities), will offer a deeper analysis of
hydrocarbon flow behaviours and how they respond to changes to
operating set points. NK asset teams can then identify flow
bottlenecks, test various optimisation scenarios, review technical limits,
and generate more accurate production forecasts.
A major concern in the E&P industry over using digital twins in large
fields is their long computation run time that makes them unfit for faster
decision cycles as required in daily operations management. KwiDF will
address this constraint by incorporating a hybrid modelling approach in
which data-driven algorithms are blended with a physics model to
speed up model run-time, aligning it with a decision-making time scale.
To keep the digital twins fresh and up-to-date, manual and time consuming tasks related to data quality checks, model update,
calibration and versioning will be automated. End users will only have to
review the bad quality models flagged by the system through
Open architecture will be the key in ensuring the longevity and
resilience of the KwiDF solution to deal with the fast pace of technology
changes and ever-evolving business needs. A well-acknowledged
observation from many digital oilfields of the past has been the
limitation, and in some cases failure, of rigid software solutions
struggling to scale beyond their coded functionalities.
Open platforms on the other hand can scale much more easily
without losing their performance and interoperability. Halliburton’s
DecisionSpace 365 platform underpinning the KwiDF solution
exemplifies this principle. The platform offers flexibility to tailor and grow
digital solutions through its open, technology-neutral, modular, and
interoperable architecture. The underlying technology building blocks
(data integration, business rules, analytics, workflow orchestration and
visualisation) accelerate the solution deployment and time to value.
The ultimate measure of KwiDF success, however, will lie in how
well it gets adopted by the organisation. End users will not just need to
embrace the value of the system, but also be able to acquire the
necessary skills and knowledge to make effective use of KwiDF in their
To that end a change management programme has been put in
place to encourage solution adoption and utilisation through regular
communications, incentive schemes and on-the-job training. A
dedicated team staffed with Halliburton domain experts and IT
specialists will be formed to provide continuous mentoring and training
to the KwiDF users in running the digital workflows and conducting the
well and reservoir performance review cadence. The team will also
gather user feedback for enhancements to the solution and report
them to KwiDF management for future release planning.
In conclusion, KwiDF Phase 1 delivered a strong engine for digital
transformation to KOC, generating momentum toward an efficient, agile
and data-informed operating model. Phase 2 will further expand and
accelerate that transition by unlocking newer opportunities for efficiency
gains through smarter and more automated work processes and
fostering the digital capabilities of the KOC workforce. Contact Us.