Javid, Khalid (ADNOC Offshore) | Ettireddi, Srinivas (ADNOC Offshore) | Mokhtar Hafez, Yahia (ADNOC Offshore) | Hossni Ali, Mohamed (ADNOC Offshore) | Marin Centurion, Pedro Ronaldo (ADNOC Offshore) | Gonzalez Cerrada, Luis Oscar (ADNOC Offshore) | Mohamed, Mohamed Sayed (ADNOC Offshore) | Zahaf, Kamel (ADNOC Offshore) | Ibrahim Alhosani, Khalil (ADNOC Offshore) | Al Qamzi, Abdulla Gharib (ADNOC Offshore)
This Green Field was recently commissioned and it was put on production last year. It is a model Digital Oil Field having two artificial islands built to drill all its wells with smart completions like ICVs, ICDs and Permanent Downhole Gauges in all Oil & Gas Producer Wells. This paper will describe the benefits of real-time data utilization for better and most efficient Field/Wells Monitoring along with Better and quick decision-making. Flow tests are performed 2-3 times a week using Multi phase flow meter (MPFM) for each of its wells.
Smart and Innovative Dashboard have been created for best screening and grouping of wells as per predefined business rules and alerting Asset Engineers for any wells, which are close to violating any of the Reservoir Management Guidelines, and therefore timely decisions, are made to avoid those violations. Miscible Gas Injection was started from the early days of Field life. Gas Tracers are planned to be injected by the end of this year to achieve the successful and improved surveillance and understandingly Reservoirs and better plan the future wells locations and completion strategy.
All Field/well Shut Down duration opportunities are utilized for Pressure Build-up analysis for Oil Producer wells and therefore considerable cost of running Memory gauges and intervention operations is also saved.
Successful Digital Oil Field is a result of collaborative and multiple discipline Team Work. Lessons learned and recommendation for any new Digital Oil Field are also presented in the paper.
Innovative Dashboards have been created to for best screening of wells and alerting for any wells, which are close to violating any of the Reservoir Management Guidelines, and therefore timely decisions, are made to avoid those violations.
The standardized data repository is developed as data integration layer using OSI PI platform products to seamlessly merge real time data with manual data to create a single data reference architecture. This has been a powerful enhancement to ensure a single version of the truth.
Al Jenaibi, Shaikha (ADNOC) | Al Mzaini, Tasnim (ADNOC) | Saputelli, Luigi (ADNOC) | Hafez, Hafez (ADNOC) | Mata, Carlos (ADNOC) | Narayanan, Ram (ADNOC) | Mogensen, Kristian (ADNOC) | Mohan, Richard (ADNOC) | Charles, Frank (ADNOC) | Mammadov, Zohrab (ADNOC) | Escorcia, Alvaro (Frontender) | Mijares, Gerardo (Halliburton) | Rodriguez, Jose (Halliburton) | Hernandez, Cristina (Halliburton)
Meeting energy demands and generating profit to shareholders is a continuous quest for oil and gas companies. Production and business planning in integrated oil and gas operating companies is a complex process involving numerous organizations, historic data collection, modeling, prediction, and forecasting.
Global oil demand has led to the development of new smarter drilling, completion, reservoir management technique and technology to optimize reservoirs production. The production of Kuwait Oil Company (KOC) has reached 3 MMBOPD and KOC’s 2030 vision is to boost the production to 4 MMBOPD. In order to achieve this vision, KOC has started several technical projects and development plans. One of these projects is the North Kuwait Integrated Digital Oil Field (NK-KwIDF) a full-fledged Field project implemented in KOC.
This Paper will discuss the scale, complexity, technology used, and advantage of using the NK-KwIDF. The North Kuwait (NK) asset has five fields, around twelve hundred active wells, and seven Gathering Centers (GCs). A complex network of pipeline, trunk line, and manifold are used to connect these twelve hundred wells to GCs. In order to optimize the production from NK every barrel of production opportunity has to be considered by optimizing suitable wells and minimizing downtime from each field, resulting the development of an extensive surface network model. The extensive surface network model takes into consideration of each and every details of field e.g. pipelines, manifolds, details of GCs and wells. For each and every well in NK assets a well model is prepared considering all PVT parameters, completions, and surface co-ordinate and finally connected to surface network model with all piping information.
Once the extensive surface model was prepared, several integrated workflows were developed in order to efficiently run the surface model and analyze the output from the run. Some of these workflows are ESP Optimization and ESP Analysis workflows, which have capability to identify the Oil Gain Opportunities and diagnose ESP performance. The identify opportunities are logged into ticketing system, which monitors the life cycle of the opportunity right from the identification till implementation into the field for Oil Gains.
The full-fledged development of NK-KwIDF took almost 3 years from the day it was started, as a pilot project with 133 wells. When an excellent result in terms of production optimization and downtime minimization was recorded from the pilot project, the pilot project was expanded to full-fledged field project. The NK-KwIDF project gave an outstanding result of Oil gain from well level as well as Network level optimization. It established an excellent reputation in the oil industry where it was a source of attraction for many NOC’s and IOC’s to visit and follow the flag ship for their development and implementation of digital field technology.
Mohamed Latif, Mohd Anwar (ADNOC Onshore) | Bedewi, Mahmoud (Halliburton) | Abdulayev, Azer (Halliburton) | Al Saadi, Noura (ADNOC Onshore) | Mohammed Saleem, Babar (ADNOC Onshore) | Al Bairaq, Ahmed Mohamed (ADNOC Onshore) | Al Ameri, Ammar Faqqas (ADNOC Onshore)
A giant gas field consisting of six stacked carbonate reservoirs of Lower Cretaceous age with gas caps and non-associated gas where the production follows a depletion scheme is discussed. The field has a production history of more than 30 years with more than 150 gas condensate wells flowing to a common surface network, which means production decline is inevitable.
This study assesses various mitigation actions to extend the plateau or minimize the anticipated inevitable production decline, and optimize costs while adhering to a service level agreement (SLA) with the consumer gas plant.
This paper illustrates how the use of an integrated asset model (IAM) as a digital twin of the actual asset can help provide a holistic approach for evaluating critical investment decisions.
The proposed mitigation actions were mainly focused on surface facilities because gas fields are sensitive to backpressure; the mitigation actions were primarily geared toward reducing backpressure to remedy the anticipated production decline.
Gas plant inlet/outlet pressure reduction proved to provide significant plateau extension. This finding was verified by means of field trials. Intermittent and weak producers responded positively to the implementation of wellhead compression during the IAM simulation; consequently, a pilot was implemented in the field to verify the simulation conclusion. IAM also proved that adding 20 new infill wells would help accelerate gas production, if necessary; but, it requires further economic justification before implementation.
Simulating scenarios, such as the segregation of wells currently sharing flowlines, had a minor effect to overall field production. A previous reconfiguration of compressors within the compression stations proved beneficial in mitigating production decline and accelerating gas volume. However, because of operational risks and associated costs, future reconfigurations showed minimum impact.
A significant portion of the study was focused on modeling the downtime of various components of the asset surface facilities as per the integrated shutdown plan (ISDP) and identifying alternative routes to minimize overall gas production disruption and to adhere to the SLA commitment.
The focus on precisely simulating the operational side of the field was enabled by the use of IAM as a digital twin of the actual asset. In addition to the usual simulation benefits, such as the assessment of various sensitivities before implementing significant investments in real life, this holistic approach can help realize cost-saving opportunities and help ensure future adherence to the contracted gas rate.
Aladsani, Amna Yaaqob Khamis Salem (ADNOC Onshore) | Alghafli, Afra Hamad (ADNOC Onshore) | Al Kaabi, Sultan Hamdan (ADNOC Onshore) | Mcneilly, Kevin Dean (ADNOC Onshore) | Akhtar, Mohamed Masud J. (ADNOC Onshore) | Tripathi, Deepak Tripathi (Weatherford) | Alkuwaiti, Hamda (Weatherford) | Soni, Sandeep (Weatherford) | Isambertt, Jose (Weatherford)
This paper discusses a production efficiency improvement (PEI) case study using an Integrated Asset Model (IAM) in a super-giant brown field consisting of more than a thousand well strings producing from multi-layered reservoir with different properties. This paper discusses various scenarios that were considered to carry out production efficiency improvement and system bottleneck identification using IAM model integrated within digital framework consisting of automated workflows and advanced data integration.
IAM solution was implemented in a super-giant brown field to help users to carry out complete system-analysis to assist in delivering production-mandates, identifying sustainability and removing potential bottlenecks for improvements.
This solution incorporates integration of validated well and network models within a digital-layer, in which various analytical-processes and workflows are automated and integrated with multiple corporate-data-sources. This centralized production-optimization based collaborative-platform enables user to carry out various scenarios while taking into account different operating constraints. Validated and calibrated well and network models were integrated within these workflows, updating them on daily basis, thereby providing representative well and network performance parameters.
This paper discusses several case studies that were carried out utilizing an integrated asset model, thereby achieving fundamental business objective of production efficiency improvement. For this purpose, full field network models consisting of more than a thousand calibrated well strings were analyzed within a digital IAM framework.
Various what-if scenarios were adapted to conceptualize an engineering approach in which various reservoir, well and facility level guidelines were incorporated for identifying true potentials of the system. This holistic approach provided users the capability to carry out a detailed analysis to achieve various key production objectives such as reducing production deferrals, compensating production shortfalls, identifying total system capacity and thereby enhancing production efficiency.
Key challenges and recommendations for improving production efficiency and establishing standardized well potential determination methodology were also highlighted from the case study. Lastly, identification of the true production limits of the reservoir, wells, and the surface network were made possible which is fundamental to the delivery of the long term field development plan.
Identifying true capacity at the well and field level is a challenging task in a field with more than ten development area with completely different fluid properties and production capacities. A standardized IAM solution approach made this estimation possible. This approach also helped in minimizing potential production deferment thereby leading to cost optimization of total system.
The Production Assurance Tool is developed to calculate the potential oil production from any field for different operational scenarios considering well potential and pipeline network limitations. This Tool represents integration between the pipeline hydraulic model and the performance of the production wells. The developed tool utilized PIPESIM software to model the pipeline network and Microsoft Excel as database for well performance in the format of lift curve, applying reservoir constraints and best reservoir management practices and as a general user interface for inputs and results. The programming script is performed by visual basic code to link PIPESIM with Microsoft excel to run number of iterations until the net system capacity is concluded. The challenges in each field determine the objective and configuration of the tool.
Desai, Sameer Faisal (Kuwait Oil Company) | Al Jadi, Issa (Kuwait Oil Company) | Al-Ghanim, Wafaa (Kuwait Oil Company) | Franco, Francy Milena (Schlumberger) | Khor, Siew Hiang (Schlumberger) | Zhang, Qiong Michael (Schlumberger)
This paper discusses the development of a truly integrated asset model for the Greater Burgan oilfield in Kuwait linking multiple wells, pipelines networks, and process facilities for achieving integrated operational excellence in the South and East Kuwait asset of Kuwait Oil Company. A water handling facility model comprising of two effluent water disposal plants, a crude oil export pipeline network and a water injection network model are also incorporated into this integrated asset model. The main objective behind the development of this integrated asset model is to enable better asset management, faster and more precise decision making and enhancing the hydrocarbon flow path all the way from the reservoir till the export point.
The new integrated asset model was developed from a model centric approach involving construction and calibration of over 1500 well models. All wells were then linked to their network models comprising of pipelines totaling more than 10,000 km. The well and network models were integrated with the respective process facility models of the 14 gathering centers located in the field and finally tied to the crude export, water disposal and water injection systems. The results of the integrated wells to process facility models such as pressure gradient, temperature gradient and erosional velocity ratio gradient across the production network can be plotted or visualized on the Geographic Information System (GIS) map.
Integration of the vast number of wells and network models with the 14 crude processing facilities in a single IAM platform provides comprehensive understanding of flowing paths spread across the giant Burgan field and proves its utility as an effective flow assurance tool. The IAM platform also provides engineers and management an effective tool for analyzing well potential, identifying under-performing wells, spotting clusters of high water cut wells, singling out back pressure effected wells and locating system constraints. Thereby the proven IAM provides valuable information for effective production optimization and long-term surface facility development plans.
The IAM platform is designed for use by Reservoir, Production, and Process Engineers as well as Operations, Business Development, and Asset Management teams. Engineers can evaluate various scenarios to improve production and operation performance such as choke increase or decrease, re-routing wells between manifolds, adding new wells into the system, and decision on slots for connecting new wells to the plant headers. The IAM also enables asset teams to forecast injection rates, review the impact on the entire injection network in terms of pressure distribution, and conduct "what if" scenarios leading towards complete asset optimization.
Desai, Sameer Faisal (Kuwait Oil Company) | Al Jadi, Issa (Kuwait Oil Company) | Al-Ghanim, Wafaa (Kuwait Oil Company) | Al Sabea, Salem H. (Kuwait Oil Company) | Al-Haddad, Saud M. (Kuwait Oil Company) | Franco, Francy Milena (Schlumberger) | Khor, Siew Hiang (Schlumberger) | Bodwadkar, Suhas V. (Schlumberger) | Saxena, Aditya (Schlumberger) | Zhang, Qiong Michael (Schlumberger) | Hapsari, Hairuni Safri Tri (Schlumberger) | Morales, Fernando (Schlumberger) | Halabe, Vijaya (Schlumberger)
Several efforts have been made in the past for generating an Integrated Asset Model (IAM) for the Greater Burgan field in Kuwait with mixed results on sustained utilization and benefits. A new effective full field Integrated Asset Model has now been developed within an Integrated Operational Excellence (IOX) program towards Digital Transformation of the Greater Burgan field. A proven model centric approach has been adopted to bring multiple interdependent wells, pipelines networks, and process facilities models together into one single truly integrated asset model. The IAM platform also includes a water processing facility model which consists of 2 effluent water disposal plants, a crude oil export pipeline network and a water injection network model. Development of this integrated wells-network-facility-crude export-water processing facility-water injection network model incorporating the 14 gathering centers in the South and East Kuwait (SEK) asset focused on providing all the essential valuable inputs to business processes for better asset management, faster and more accurate decision-making and optimizing the hydrocarbon flow path all the way from the reservoir till the export point. The assessment was done at full field level where the complete system constraints, interactions and back pressure effects between more than 2000 different wells were fully accounted up to the crude processing facilities. The availability of this fully integrated asset model with up-todate calibrated wells and network models and process models enables Kuwait Oil Company (KOC) engineers to better understand current well performance and production potential, identify any possible bottlenecks imposed by the large complex surface network and process facilities of Greater Burgan Oilfield. The simulated results such as pressure gradient, temperature gradient and erosional velocity ratio gradient across the production networks are presented on the GIS map for easy opportunity identification.
Al Jadi, Issa A. (Kuwait Oil Company) | Desai, Sameer Faisal (Kuwait Oil Company) | Al-Ghanim, Wafaa (Kuwait Oil Company) | Al-Wazzan, Roqaya M. (Kuwait Oil Company) | Al Sabea, Salem H. (Kuwait Oil Company) | Al Haddad, Saud M. (Kuwait Oil Company) | Franco, Francy Milena (Schlumberger) | Khor, Siew Hiang (Schlumberger) | Saxena, Aditya (Schlumberger) | Zhang, Qiong Michael (Schlumberger) | Hapsari, Hairuni Safri Tri (Schlumberger) | Elayaat, Ahmed A.Fouad. (Schlumberger) | Bodwadkar, Suhas V. (Schlumberger)
A proven and effective integrated asset modelling (IAM) approach has been adopted to bring multiple interdependent wells, pipelines networks, and process facilities models together into one single truly integrated asset model for the Greater Burgan Oilfield in Kuwait. The integrated wells-network facility models via the IAM platform also includes a water processing facility model which consists of 2 effluent water disposal plants; a crude oil export pipeline network and a water reinjection network model. This paper describes how a representative integrated asset model was developed for the Greater Burgan Oilfield through a model centric approach executed within an Integrated Operational Excellence (IOX) Program towards a Digital Transformation initiative by Kuwait Oil Company (KOC) South and East Kuwait (S&EK) Group together with Schlumberger. It also describes how this tool enables the asset teams to evaluate different operating scenarios to further enhance well performance and the overall asset productivity via rerouting well flow path to an appropriate header, identifying well workover opportunities, reevaluating artificial lift design, adding future wells (for field development) and comprehensive understanding of well integrity and flow assurance studies. The assessment was done not only at a gathering center (GC) level but also asset-wide level where the complete system constraints, interactions and back pressure effects between more than 2000 different wells were fully accounted. The simulated results such as pressure gradient, temperature gradient and erosional velocity ratio gradient across the production networks are presented on the GIS map for easy opportunity identification. The availability of this fully integrated asset model with up-to date calibrated wells and network models and process models enables KOC engineers to better understand current well performance and production potential, identify any possible bottlenecks imposed by the large complex surface network and process facilities of Greater Burgan Oilfield.
Desai, Sameer Faisal (Kuwait Oil Company) | Rane, Nitin M. (Kuwait Oil Company) | Al-Shammari, Baraa S. (Kuwait Oil Company) | Al-Sabea, Salem H. (Kuwait Oil Company) | Al-Naqi, Meqdad (Kuwait Oil Company)
Kuwait Oil Company initiatives for ushering in a new era of digital transformation of its assets to intelligently and optimally manage the Oil and Gas fields were successfully realized with the completion of three pilot projects entitled Kuwait Integrated Digital Fields (KwIDF). This paper discusses major achievements of the Digital Oilfield technology implemented in Burgan KwIDF project and provides an insight on the challenges in operating it.
The Burgan KwIDF pilot successfully transformed GC-1 production asset into a fully instrumented DOF comprising of digital instruments and infrastructure installed at well site and the production facility. Real-time production data is transmitted to a state of the art collaboration center that integrates data continuously with automated workflows for validation, modeling and tuning of well and facility models. Right time decision support information generated from smart visualization tools allow quick actions for production optimization, well and facility management in a collaborative work environment.
There is persistent value realization from KwIDF technology implemented in Burgan field. It has generated substantial cost savings with faster response time in restoring production and reduction in non-productive time. Driven by the digital environment asset production has sustained at target as production gain opportunities are capitalized and losses compensated quickly.
Over the period of time with experience in utilizing the DOF technology it has been observed that the technology sustainment is dependent on the technology providers to a large extent. The main components that require their continuous support are the digital instruments, proprietary software, hardware and related infrastructure. Technical expertise in each domain is necessary for ensuring continuous and smooth operations in the field, wellsite and collaboration centers. Development of an integrated team of domain experts is crucial for successfully managing the DOF operations. Change management initiatives for developing an in house user champion team is mandatory for ensuring sustainment. The important lessons learned and solutions are discussed in detail.