In oil & gas operations, optimisation opportunities of the field production efficiency and performance can be developed and guaranteed by combining monitoring and control elements in so-called "value loops??. Such an approach is possible when reliable and consistent data and information from the complete production system are provided to the right users at the right time.
This paper presents existing field applications of advanced data validation and reconciliation (DVR) techniques which use all available information and measurements in order to provide reliable and consistent data from reservoir to oil and gas delivery.
Implementation and application of advanced DVR to offshore production installations located in Middle East and West Africa are described in detail with specific focus on well production determination and gas balancing and measurements.
Specific highlights are given to advanced DVR models development, field implementations and on results obtained in continuous well flow rate calculations, in equipment monitoring and topside measurements.
By combining sensors, flow measurements and modelling, advanced DVR has permitted to question and validate measurements but also multiphase metering information, equipment operation and flow models parameters.
Operational field experience gained by TOTAL demonstrates that online use of advanced DVR techniques allows to:
This gives the user the possibility to improve well production figures and environmental reporting and also the opportunity to optimize equipment operation and instrumentation maintenance.
The promise of an "Intelligent Energy?? initiative is premised both on the availability of real-time data, and on improving real-time communications between the field and the office. However, acquiring, organizing, and making sense of real-time data for field production management poses a number of challenges for any individual surveillance engineer. For an asset team working collaboratively, the challenge of efficient and effective data monitoring and the performance of optimization workflows can be even more demanding. Many production workflows require an engineer to coordinate data flows between numerous, diverse, and frequently siloed systems and applications. Studies have shown that approximately 50-70% of an engineer's time is spent finding, gathering, and managing data for use in these different applications1. This non-productive time can be drastically reduced by defining standard production workflows, by implementing an automated system to execute these prescribed workflows, and by ensuring that the data sources are well defined and accessible.
A well-designed, thoughtfully implemented, and automated workflow ensures that all the relevant data is available "at the fingertips?? of each member of the asset team, reduces the likehood of input errors, and removes the burden of data management from engineering personnel. These automated workflows allow knowledge workers to focus on value-added engineering tasks. In addition, the design and implementation of automated and configurable workflows creates a transparency and consistency in work processes that can be customized to the unique needs of each asset.
This paper presents an asset-based collaborative project that includes:
The core enabling technology that allows these automated workflows is a vendor-neutral integration platform that dynamically links diverse data sources and software applications currently in use for production monitoring and optimization.
BP has deployed early warning systems that monitor heavy machinery, markedly increasing the reliability, operational integrity, and performance of equipment in BP's operations. Early warning allows BP to more effectively schedule maintenance (with costs of planned maintenance typically being a fraction of the costs of emergency repairs) and plan to minimize any production loss during the work through reconfiguration and feed rerouting. The company's initial trial generated value of $2 million during the trial alone, at a cost of only $50,000. Additional trials provided further savings of almost $3 million through detections such as pump seal problems, failing instrumentation, control problems, and turbine fouling. These striking benefits led BP to plan a significant deployment across the company.
In just over a year, BP has made significant implementations at more than half of its facilities in one business segment and online pilots in all other business areas. Millions of dollars have already been saved; BP's goal of significantly reducing unplanned maintenance is well on its way to being realized. Far fewer experts are required to spot developing problems than with traditional data monitoring methods, this can now be done by a skilled technician; so more problems are caught. Quick-win maintenance savings more than paid for the technologies in the first year, and the safety benefits in a potentially hazardous environment are priceless.
BP's aggressive adoption of wired and novel wireless technology to capture more measurements has significantly increased the volume of data available. This wealth of data put BP in an even better position to leverage predictive analytics technology. The technologies' data-driven approach has many advantages over the traditional trending or first principles models used in the past. It's generally faster to implement, easier to maintain, does not require sophisticated engineering knowledge, and makes use of a wealth of existing but unused data, representing a breakthrough in the area of equipment health.
Recent advancement in well technologies, communications and field instrumentation has made it possible to achieve total asset awareness and optimize operations over the field's development lifecycle. This is achieved by leveraging fields' real-time data for continuous monitoring and right-time response throughout the development processes. Right-time response has two components: Fast Interventions being done today as a product of an intra-process optimization, and Strategic Interventions based on more detailed modeling, discussed in the next steps section. The results of this integration have led to optimized drilling operations and well placements, increased production rates, and improved reservoir management and production operations. Real-time integration in the business processes, in turn, has introduced further opportunities for higher hydrocarbon recoveries and lower operating costs and capital expenditures. In the industry, integration of the various digital surface and subsurface technologies into E&P business processes has been given different names, such as Smart fields, Intelligent Field (I-Field), Digital Oil Field Of the Future (DOFOF), integrated field (i-field) and Integrated Operations (IO). Four major projects have been implemented in Saudi Aramco to take advantage of the digital field development opportunities in major E&P upstream business processes.
This paper provides an overview of Saudi Aramco's implementation approach and experience in integrating real-time data in the upstream business processes, such as Drilling and Completions through Real-time Drilling Operation and Geosteering, Production Operations and Reservoir Management through Intelligent Field, and Development Planning and Optimization through Event Solution.
Spears and Associates (2009) estimated spending on drilling and completions at over USD 250 billion in 2008. With rig costs estimated to consume 37% or USD 92.5 billion of that spending, every effort to reduce drilling time has a direct impact on our bottom line. Estimates of non-productive time (NPT) ran from 15-40% or USD 14-37 billion, depending on well type and operator. The causes were varied and included technical and non-technical challenges such as wellbore stability, stuck pipe, weather, logistics, etc. Obviously any effort made to reduce NPT will tremendously impact bottom line spending.
Given that causes of drilling inefficiencies are often known and predictable, why do we struggle to improve our results? The challenge is often one of fundamental knowledge management, which includes: difficulty in using historical data, lack of access to relevant data, and the inability to effectively correlate multiple wells in a single view.
Imagine how much more efficient the drilling process would be if you could plan future wells based on nearby offset wells populated with important drilling knowledge from a living drilling knowledge base. The knowledge base would contain all surface drilling parameter data, BHAs, bit records, MWD/LWD data, drilling events, lessons learned, best practices, etc., associated with each well. Data from new wells added to the knowledge base in real time make it more robust, allowing for tracking of position with respect to the shared earth model and updating of the model while drilling. All pertinent data could be displayed side-by-side, allowing correlation of multiple wells by formation, depth or time, in one, two, or three dimensions. Comparison of multiple wells in a single view facilitates better well planning through anticipation of problems and mitigation of risks. This comparative ability leads to an increase in drilling efficiency and a decrease in rig time, which can result in reduced spending.
This paper illustrates techniques for improving collaboration and analysis of real-time and historical drilling data, increasing the cost effectiveness of drilling efforts, and presents a case study highlighting the achievable benefits.
The Smart Fields programme has been active in Shell over the last decade and has given large benefits. In order to understand the value and to underpin strategies for the future implementation programme, a study was carried out to quantify the benefits to date. This focused on actually achieved value, through increased production or lower costs. This provided an estimate of the total value achieved to date. Future benefits such as increased reserves or continued production gain were recorded separately.
The paper describes the process followed in the benefits quantification. It identifies the key solutions and technologies and describes the mechanism used to understand the relation between solutions and value. Examples have been given of value from various assets around the world, in both existing fields and in green fields. Finally, the study provided the methodology for tracking of value. This helps Shell to estimate and track the benefits of the Smart Fields programme at company scale.
The latest generation of Subsea Electronics Modules used for control & monitoring of subsea producing wells is able to offer great improvements in data bandwidth for "smart" subsea oil & gas applications, providing very high speed fibre optic links to surface facilities. These devices provide IP enabled data links, with transparent interfaces to subsea sensors and surveillance systems.
Even with such communications advances, the challenge is to interpret this data effectively to provide added value to the operators and prevent data overload. One area of added value is in Flow Assurance and the application of on-line flow assurance techniques to better understand the behavior of the produced fluid/gas and the effects that the various change agents have on production as well as the infrastructure. Also, with the growth of high-speed global communication networks, linked to Smart Operations centers, and the improvements in data security, the use of Remote Condition Monitoring & Diagnostics techniques to provide interactive support and proactive maintenance is a key concept for integrated operations based on expert system and historical data sharing. This approach is a fundamental driver in enhancing the efficiency of a facility through collaborative data and knowledge sharing.
This paper will describe the practical details and challenges for a service provider of setting up a Remote operations center, establishing connectivity and data security / integrity as well as setting to work the day to day operations and manning procedures. The paper will also describe a new generation technology and product for subsea projects, which provides a system micro-controller function as well as acting as the data communications router.
The Subsea e-Field starts with remote monitoring. Remote monitoring of subsea oil and gas production facilities should, in principle, be straightforward. We require connectivity to a facility, allowing data collection and aggregation, which leads to data analysis, and affords the opportunity to improve recovery/performance with additional tools. There are many precedents in onshore and mobile applications as can be seen in the illustration in Figure 1.
In this illustration there are some examples of remote condition monitoring within the GE organisation. You will see that these technologies have been applied to both asset management for a mobile fleet, and to the long-term monitoring of in-flight data from the GE high by-pass turbo-fan engines, such as, for example, those on the Boeing 777. On landing all the flight data is transmitted to a central i-Centre. Here, through a process of automatic diagnosis and predictive maintenance, this critical asset for the airlines given an increased "on-wing?? time.
Similarly there are examples from fixed installations of gas turbines where some 1000 gas turbine sets are monitored routinely from i-Centres in Atlanta and in Florence.
Lastly we can see an example from the rail industry in the United States where over 10,000 locomotives on the track can be monitored in their day-to-day operation, which allows increased utilisation and, more importantly, avoids the all-important failure while the unit is on the track, part way through its journey.
Implementations of smart-field strategies with intelligent completions, i.e., interval control valves and interval control devices, are growing in the oil industry. Yet, there is still resistance by some companies because of concerns for (1) provable long-term value in terms of oil recovery and returns; (2) risk of valve failures affecting well integrity and performance; (3) lower returns of actual results relative to predicted results (i.e., overoptimistic projections, often from simulation); and (4) uncertainty as to the most effective future operational practices. This paper presents a systematic analysis of well rates and pressures as predicted by simulation for a long horizontal well. The paper investigates long-term value, analyzes impact of valve failure on production, provides estimates on the impact of reservoir uncertainty on performance, and demonstrates production improvements from effective operational control procedures for the horizontal well, for a multi-lateral well, and for a 20-production well waterflood. The paper validates and implements a methodology using simulation-based analysis and automated procedures to optimize valve-control strategies: oil production is maximized, while water production is better managed. Two control strategies are investigated and compared against a do-nothing approach: a fixed control strategy and a flexible control strategy.
In common with many organizations in the industry, BG Group faces the challenge of how to identify colleagues with the most relevant expertise, how to learn the lessons of experience, and how to support BG Group's global Integrated Operations initiative ((1) Collison & Parcell, 2004)). In earlier times 'Knowledge Management' focussed on capturing structured information and storing it in corporate repositories. But a wider set of collaboration possibilities and capabilities is needed to capture the abundance of ways in which people's insights can be expressed and to cement new ways of working.
Through a programme of concept pilots, BG Group's Global Advanced Technologies team has been working across the business to introduce a range of Web 2.0 social technologies. The fundamental building block of the social web is the individual's person-profile, listing their experience and affiliations. From that rich description of the person, all else follows; person to person networking, the formation of online communities, access to specialized libraries through built-in wiki spaces, instant meetings from the desktop with video-conferencing support, individualized communication through blogs, targeted information feeds through RSS, and social search with shared book-marking of resources.
Now and in the future, people can benefit from finding out 'who knows who' or 'who knows what' and 'what is significant' - as expressed by their own collective intelligence. This paper will share success stories and feedback from the programme.
Mabian, Andrew Francis (Salym Petroleum Services B V) | Hagelaars, Ad (Salym Petroleum Development) | Diamond, Joe (Salym Petroleum Development) | Beliakova, Natalia Yurievna (Shell Intl. E&P BV) | Genkin, Jean-Marc Patrick (Salym Petroleum Development) | Pickles, Mike Robert (Salym Petroleum Development)
Salym Petroleum Development (SPD) has embarked on an ambitious Oil Field Management Improvement Program with as key objectives to:
The goal of this paper is to present SPD's approach to Oil Field Management in the context of a West-Siberian water flood. Oil Field Management is based on the Value Loop (Figure.1) where data is acquired from physical assets (reservoir, wells, facilities) and subsequently incorporated into models that drive the optimization of these same physical assets. The value loop has different cycling times ranging from seconds to decades (Figure.2). Traditionally, the shortest value loop is called Real Time Optimization ("RTO??) with a time span measured in seconds, minutes and hours, followed by Well and Reservoir Management ("WRM??) with a time span measured in weeks, months or years, and finally Hydrocarbon Development Planning ("HDP??) with a time span measured in years, if not decades.