Haider, Bader Y.A. (Kuwait Oil Company) | Rachapudi, Rama Rao Venkata Subba (Kuwait Oil Company) | Al-Yahya, Mohammad (Kuwait Oil Company) | Al-Mutairi, Talal (Kuwait Oil Company) | Al Deyain, Khaled Waleed (Kuwait Oil Company)
Production from Artificially lifted (ESP) well depends on the performance of ESP and reservoir inflow. Realtime monitoring of ESP performance and reservoir productivity is essential for production optimization and this in turn will help in improving the ESP run life. Realtime Workflow was developed to track the ESP performance and well productivity using Realtime ESP sensor data. This workflow was automated by using real time data server and results were made available through Desk top application.
Realtime ESP performance information was used in regular well reviews to identify the problems with ESP performance, to investigate the opportunity for increasing the production. Further ESP real time data combined with well model analysis was used in addressing well problems.
This paper describes about the workflow design, automation and real field case implementation of optimization decisions. Ultimately, this workflow helped in extending the ESP run life and created a well performance monitoring system that eliminated the manual maintenance of the data .In Future, this workflow will be part of full field Digital oil field implementation.
The time taken to safely optimise a reservoir produced by artificial lift can be measured in weeks or months.
Typically the well by well process is as follows:
• Well testing
• Amalgamation of the well test data with down hole gauge and ESP controller data
• Analysis of the data to find the existing operation conditions
• Analysis of the ESP pump curve operating point and optimisation limitations
• Sensitivity studies in software to assess the optimum frequency and WHP
• Notification for the field operations to action the changes
• Further well tests to verify the new production data.
• Analysis of the data to ensure the ESP and well are running optimally and safely at the new set points
New technology enables this process to be performed in real time across the entire reservoir or field, significantly shortening the time to increased production and enabling real time reservoir management.
Each artificially lifted well in the reservoir was equipped with an intelligent data processing device programmed with a real time model of the well. The processors were linked to a central access point where the operation of field could be remotely viewed in real time.
Each well's processor was provided with a target bottom hole flowing pressure to enable the optimum production of the reservoir. The real time system automatically compared the desired target drawdown values with the capability of the pumping system installed in each well, and automatically suggested the optimum operating frequency and well head pressure to achieve the target. Where the lift system was not capable of producing to the target bottom hole pressure, a larger pump was automatically recommended. As production conditions change the system adapted its recommended operating points to compensate and maintain target production.
This paper discusses three case studies where real time optimisation and diagnosis lead to improved production from the reservoir.
Research on measuring the ice impact pressure on icebreaker hulls began inthe late 1970's, and its focus was to determine the magnitude of the impactpressures and to obtain long-term statistics of the impacts. Increasedcomputing power in the 1980's allowed the recording of time-histories onmultiple sensors that led to the development of the pressure-contact arearelationship. The aim of these systems, however, was to understand theice impact process and to provide guidance to design engineers. Thispaper presents a new hull structure monitoring system that can benefit both theship designers and operators for ships operating in ice-covered waters. With this system, the ice load monitoring system can measure and process theice impact loads immediately after each impact in near real-time. Theimpact measurements are used to estimate the resulting stresses on the hullstructures which are then compared to the allowable stresses. This systemcan provide meaningful near real-time feedback to the ship's crew of thestresses due to ice impact compared to the allowable stress. Thisinformation can assist the ship's crew in making informed decisions for safeand efficient operations in ice. The main focus of this paper is on themethodology for assessing the hull structural responses under ice impact andthe presentation of this information to the ship's crew.
The increase in offshore activity in harsh weather areas of the worldpresents a major challenge for those involved in the management and executionof lifting operations. This challenge becomes all the more important whenpersonnel are being transferred by crane. This paper examines some of the newtechnologies and operational philosophies that promise to help operators meetthese new challenges. This includes motion monitoring technology developed inNorway that provides accurate real-time data on vessel responses for mariners,and crane operators, allowing them to increase the safety and extend the limitsof lifting operations.
Crane operational downtime has a major financial impact on arctic projects.Therefore there is pressure to maintain continuity of lifting operations. Thisproven technology - the Deck Motion Monitor (DMM) and the Arctic personnelcarrier - allows the safe transfer of cargo and personnel for a higherpercentage of time and reduces the time spent waiting for an optimal weatherwindow.
The oil and gas industry is increasingly focusing its interests andactivities on areas that are prone to ice cover, in the form of sea ice andicebergs. The authors have noticed two significant trends with respect to theice charting to support operations in oil and gas operations:
As a consequence, the authors have embarked on a project to address thisdeficiency by identifying minimum standards and best practices for theprovision of ice information derived from satellites for companies operating inthe polar and sub-polar regions. The development of a guideline governing icecharts is the primary focus of this project. The project has identifiedrequirements through the oil and gas project lifecycle, has matched these todifferent regions and has categorised satellite-derived ice information byservices and products. The project has reviewed current practices and willestablish a guideline with input and validation from the industry, taking intoaccount current constraints and future opportunities. Ice charting guidelineswill provide clear options to industry. Companies will be able to buildprocesses and systems around guidelines and can be assured that compliantservice providers will be compatible with their systems. Guidelines will alsoincrease access of the market to service providers, leading to increasedcompetition and lower costs. Ultimately, the knowledge of ice chartingcapabilities will be well documented so that they are not lost with staffattrition. This paper presents an overview of the ice charting guidelinesproject and its objectives, schedule, status and deliverables. This project isbeing coordinated through the Oil and Gas Earth Observation Group (OGEO) of theInternational Association of Oil and Gas producers (OGP) with initial seedfunding from the European Space Agency and Shell E&P International.
Index Terms— ice charting, ice information, sea ice, icebergs,guideline
Hydrocarbon exploration in the Arctic environment will very much depend onour ability to continuously track ice floes and forecast ice events that maygenerate dangerous loads on exploration and production infrastructure. Wepresent a first-of-its-kind computational framework which is centered aroundnear-real-time satellite imagery and incorporates real-time metocean data,providing automated analysis of such hazards in regions where moving ice ispresent. Our automated framework carries out several ongoing operations: icedetection and classification from satellite images, floe tracking from oneimage to the next, forecasting of floe trajectories beyond the observed tracks,and estimation of an uncertainty cone around the trajectory forecast. Weutilized the IBM InfoSphere™ Streams real-time analytics platform to deploy oursoftware, which made it possible for us to concentrate exclusively onprototyping algorithms, taking for granted the streaming infrastructure neededfor real-time data ingestion and flow between operators. Given our experiencedeveloping this prototype we conclude that a production-worthy, automatedtracking and forecasting capability is computationally feasible and within ourreach.
Poedjono, Benny (Schlumberger) | Beck, Nathan (Schlumberger) | Buchanan, Andrew (Eni Petroleum Co.) | Brink, Jason (Eni Petroleum Co.) | Longo, Joseph (Eni Petroleum Co.) | Finn, Carol A. (U.S. Geological Survey) | Worthington, E. William (U.S. Geological Survey)
Geomagnetic referencing is becoming an increasingly attractive alternativeto north-seeking gyroscopic surveys to achieve the precise wellbore positioningessential for success in today's complex drilling programs. However, thegreater magnitude of variations in the geomagnetic environment at higherlatitudes makes the application of geomagnetic referencing in those areas morechallenging.
Precise, real-time data on those variations from relatively nearby magneticobservatories can be crucial to achieving the required accuracy, butconstructing and operating an observatory in these often harsh environmentsposes a number of significant challenges. Operational since March 2010, theDeadhorse Magnetic Observatory (DED), located in Deadhorse, Alaska, was createdthrough collaboration between the United States Geological Survey (USGS) and aleading oilfield services supply company. DED was designed to produce real-timegeomagnetic data at the required level of accuracy, and to do so reliably underthe extreme temperatures and harsh weather conditions often experienced in thearea.
The observatory will serve a number of key scientific communities as well asthe oilfield drilling industry, and has already played a vital role in thesuccess of several commercial ventures in the area, providing essential,accurate data while offering significant cost and time savings, compared withtraditional surveying techniques.
Like any other machines, motors and generators are subject to wear and aging. The materials and components they are made from degrade over time, and if no action is taken this degradation will eventually lead to failure. In critical applications, as in the petroleum industry, a failure can have dramatic and expensive consequences. Fortunately most types of failure can be prevented by maintenance. To plan maintenance effectively, the plant operator must have accurate information about the status of the equipment. In particular, the operator has to know which components need repairing or replacing, and when.
Advances in technology and communications mean that it is now possible for decision makers to access real-time information on the condition of their motors and generators.
Accurate placement of the borehole within the reservoir and identification of features impacting producibility are key elements for success. Experience to date, shows that the drilling environment offers a good platform for high definition electrical borehole imaging. At the time of drilling, invasion and borehole wall rugosity are often minimal and electrical images generated by sensors that rotate with the drill string provide a full coverage of the borehole. It also provides an opportunity for real-time geological analysis while drilling and the decision making that is unavailable with wireline. Detailed analysis of images reveal discrete sedimentological and textural features aiding facies recognition in carbonate reservoirs. These facies can be up-scaled to facies associations and eventually used for depositional environment interpretation. This leads to wider prospect delineation and confirmation of the local geological model. The study also demonstrates the strength of early geological information in high-resolution for reducing geological uncertainty at an early development drilling program.
We show case studies from several carbonate reservoirs in which high resolution electrical images have been acquired in conjunction with reservoir navigation (well placement). From post well analysis, we can define the key criteria that help in recognition of reservoir position; correlatable sedimentary surfaces and image facies/patterns. We test the distribution of facies and sedimentological features that can be recognised in horizontal boreholes by comparison to vertical offset wells, in addition to automated facies recognition from image log responses. The development of a Sedimentary or carbonate facies steering technique using high-resolution images with a predictive and real-time interface will reduce uncertainties related to and better aid geosteering within the desired "sweet-spot?? of a variety of clastic and carbonate reservoirs.
A Predictive Maintenance Strategy based on Real-Time Systems
The optimization of preventive maintenance forms the backbone of successful proactive maintenance scheduling. This paper describes the components of a real-time information system and the modeling criteria used for a predictive maintenance strategy.
Components of a real-time system
Data Acquisition uses sensors and data conversion to measure, standardize, and transmit the operational parameters and environmental conditions.
Historian databases record the operational parameters over time. The historian database supports multiple data collection points from sensors, rig scheduling, and planned operations in SAP systems using standard protocols.
Modeling and Analysis tools use the information in the historian database to build response models and predict changes in the equipment performance. These tools include data access, algorithmic modeling, visualization, and alarm subsystems.
The predictive modeling of equipment performance uses equipment specifications, past performance, and current performance measurements. Normal operational windows are used to generate out-of-normal alarms.
All relevant operational and environmental parameters are correlated to create normalized performance curves. The trends are calculated to extrapolate changes in equipment performance and determine future failure points. The maintenance windows are matched to planned operational phases to determine the optimal windows for maintenance.