As well complexity increases, re-entry and intervention operations are becoming increasingly ambitious in both their objectives and their risk profile. At the same time, intervention and service tool operating parameters downhole are traditionally controlled by making surface adjustments based on surface readings of hook load, rpm, torque, etc. A system has been developed that measures all the physical parameters downhole at the intervention tool itself, and transmits them to surface for rig site and remote viewing, enabling real time control of intervention operations. The new system has been used with fishing tools, sidetracking systems, and a variety of different service tools. The system captures and computes all the service tool operating parameters downhole, then uses a measurement-while-drilling (MWD) tool to send selected and critical parametric information to surface. Furthermore, bi-directional capability allows parameter formats to be updated throughout the job. A great deal of learning has been acquired from operating the new system, mostly in the form of parameter detection, quantification, and job management; such as: detecting delicate and ultra-light events; quantifying actual torque and drag; managing helical lock-up, untoward vibration events, and exit window trajectory and quality. In conclusion, a significant number of runs have shown that surface and remote viewing of actual operating parameters in real time has enabled improvements in operational efficiency by improved decision-making that led to reduced job times. The purpose of this paper is to demonstrate this learning through multiple case histories. A new system provides the ability to view actual downhole parameters of fishing tools, service tools, exit tools, etc. in real time, and remotely, during re-entry and intervention operations. The system is shown to have a significant impact in removing uncertainty and driving improvements in operational efficiency. Introduction A significant portion of unplanned nonproductive time (NPT) costs are incurred during wellbore intervention operations, casing exits, fishing, milling and de-completions operations. Improving operational efficiency by avoidance of unnecessary, unproductive trips in the well during wellbore interventions leads to immediate cost savings. Reserves are often stranded in deep, complex reservoirs and due to economic or environmental constraints sometimes have to be connected from a single drill site, resulting in wellbore construction methods such as extended reach drilling (ERD) and multi laterals. The drilling industry has developed sophisticated and reliable downhole technologies to operate in extremely hostile physical environments and drill these complex three-dimensional well profiles. Wellbore intervention operations in these same complex well profiles present significant challenges as well, including manipulating mechanical service tools, often at great depth. During interventions, however, sophisticated drilling systems are missing and the tool operator is solely relying on surface measurements such as RPM, hook weight and rotary torque. Traditional surface based indicators and gauges often do not reflect what forces are actually being exerted at and around the downhole tools.
In these times of record operating costs, stakeholders place paramount importance on avoiding unnecessary, unproductive trips in the well. In well intervention applications such as milling, cutting, washing over and casing exit work, the lack of accurate information about downhole conditions often leads to wasted time and money. As wells become deeper, more tortuous and technically challenging to intervene, the need to know more about what is actually occurring at the downhole tools becomes even more critical. Traditional surface-based indicators and gauges often provide inaccurate readings of the forces exerted at and around downhole tools. This paper discusses a new, MWD-style "smart" intervention performance sub that contains a variety of sensors and electronics that gather critical downhole measurements and transmit them to surface. The smart tool affords the operator a completely new level of control with real-time decision-making capabilities that can lead to more efficient and reliable wellbore intervention jobs and significantly reduce operators' risk exposure. The paper will describe the smart tool and present several case histories where the smart intervention performance sub was integrated into well intervention bottomhole assemblies. Data from the smart tool was then transmitted using mud pulse telemetry and viewed at surface. The same data was also transmitted onshore to a real-time operating center, thus allowing a broader audience of experts to witness the early field trial applications. The field trials verified several capabilities. Vacuum filter operation could be observed in real time, casing windows could be quantified with a window quality indicator, lightweight fish could be identified in real time at the bottom of deep, deviated wells, and packer setting forces and overpull could be accurately monitored downhole in a variety of depths and deviations. This summarizes the capabilities explored during deepwater system integration tests. Introduction Well intervention jobs are specialized, often critical, operations performed by experienced and well-trained tool experts. The more critical the operation, the more accurate this statement, and never more so than when conducting casing exit and fishing operations such as multilateral (ML) junction creation, milling, cutting, and washing over. Complex well intervention operations of a critical nature bring with them an inherent element of risk. The nature of this particular risk is that unseen sub-surface conditions and events can manifest themselves as unplanned non-productive time (NPT) with potentially severe consequences for fiscal prudence. Well intervention operations cover a huge expanse of well and rig activities. The processes and techniques discussed here, however, are not yet sufficiently advanced to be applied across the whole gamut of operations, so in the context of this paper, the term "well intervention" will apply to workover systems; fishing and milling, including packer setting and recovery; casing exit systems [sidetracking or junction creation], and wellbore cleanup. Well intervention operations are traditionally performed using surface-acquired parameter measurements such as RPM and hook load; complemented by a tool expert's sense of feel and anticipation. It is well known that the industry is entering a period where such experience is becoming scarce. These factors, combined with ever-increasing well reach and complexity, act to increase the risk to wellbores. Drilling, on the other hand, has benefited from new technologies that optimize complex well construction to the extent that, compared to only a few decades ago, drilling operations have evolved into highly efficient and predictable processes. It is this drilling optimization technology that has been adapted to form the basis of a new smart intervention system that boosts performance by allowing downhole parameters to be displayed at surface to enable real-time decision-making and full process optimization in well intervention operations.
This paper describes a new intelligent well intervention performance system. One that contains a variety of sensors and electronics to gather critical downhole measurements, analyze them, and transmit them to surface for viewing in real time. It confirms that many well intervention operations, especially those that get into difficulty, suffer from a lack of accurate information about true downhole conditions, and that actual downhole conditions in deep, high-angle wells differ significantly from what is indicated by traditional physical measurements taken at surface alone. The parameters measured downhole include RPM, torque, tension and compression, stick-slip, bending stress, dogleg severity, and many others. Extensive field integration testing and early commercial deployment show how downhole tool performance information provides parametric information physically characterizing the true downhole environment. This real time information, never before seen at surface, demonstrates the potential to enable more efficient and more reliable well intervention operations while significantly reducing uncertainty and risk exposure. Several case histories are presented where the smart tool was integrated into well intervention BHA's and operations were improved by a better understanding of what is really happening downhole. Introduction The current era of hydrocarbon extraction has brought with it an astonishing transformation in the extent and complexity of three-dimensional well path geometries. As little as thirty years ago, the vast majority of wells were of a relatively simple geometry, with the most complex having an initial vertical section followed by a straight tangent section that ended with a liner dropping into a vertical reservoir section. Workovers and wellbore intervention operations in these well profiles were also comparatively simple affairs, where the biggest challenge to evaluating the operation of service tools was overcoming sliding friction in the tangent section, a situation that was generally overcome by workstring rotation and selecting the midpoint of the up and down weights from the rig floor weight indicator. Over the last few decades, that case has changed dramatically. Well profiles are now much more complex and most definitely three-dimensional. In creating these complex well profiles, the drilling industry has developed some very sophisticated and reliable downhole technologies to operate in extremely hostile physical environments.
During well construction activities, measurement-while-drilling (MWD) technology is applied to transmit sophisticated spatial and petrophysical data from downhole to surface. Used with advanced well construction tools such as rotary steerable systems, MWD technology has enabled complex, even tortuous, well profiles to be created and placed in the reservoir with great precision. However, even on these sophisticated and expensive wells, any well intervention operation process is still controlled using traditional surface-read data such as revolutions per minute (RPM), hook load, torque, etc. The ability to transmit and use downhole intervention process data in addition to surface-acquired data presents significant potential for intervention process optimization, since modern data acquisition technology close to the tool can provide not only more accurate data, but also important additional parameters not available at the surface. Examples of value-adding downhole intervention process data are bore pressure, annular pressure, weight-on-tool, tension-on-tool, torque-on-tool, RPM, workstring bending and dynamic diagnostics. Additional intervention process information on intervention hydraulics or workstring friction can be obtained by feeding existing engineering algorithms with surface- and downhole-acquired data. This paper discusses the available downhole well intervention process data and demonstrates by a number of case studies the risk reduction value of viewing these parameters in real time. Furthermore, the paper discusses factors constraining the use of the technology and gives an outlook on future developments in well intervention process optimization utilizing real-time downhole data. Introduction During the early years of the 20th century, shallow vertical wells required many months to drill. By the nineteen eighties, a 90-day well program was fairly common for an offshore well - 80 years to cut the well time by up to a third. Today, thanks to a 20-year investment in drilling optimization, a well can be drilled in thirty days. Dramatic progress has been made in target accuracy, trajectory, step-out, temperature, and even depth. The drilling optimization approach has also substantially reduced non-productive time (NPT) in the drilling arena. Well intervention, however, has not kept up; it is this sector of well operations that now has the largest potential for risk and unplanned expenditure, particularly with ambitious well trajectories and in deeper waters. A significant portion of today's unplanned NPT costs accrue during well intervention operations, de-completions, casing exits and fishing operations. Many of these costs are preventable. Currently, well intervention decisions are still based on traditional surface-acquired data such as RPM, hook load, and rotary torque. The potential for intervention process optimization and with it, the ability to substantially mitigate risk in almost any intervention operation, is significant. Optimization Essentials Much as drilling optimization has transformed the drilling industry, so, too, can real-time downhole data acquired from an intervention bottom hole assembly (BHA) - especially when combined with surface acquired data - optimize the well intervention process by facilitating decision making in real-time and enabling intervention parameter management. Creation of an intervention optimization model requires a number of essential elements.○Suitable well intervention operations○Planning and modeling○Downhole data acquisition○Data transmission○Control system○Intervention parameter management Assembling these elements and performing system integration enables real-time intervention parameter management. How can that be achieved? The concept is to utilize data very similar to that generated in MWD operations and translate the data to well intervention operations, to provide an accurate picture at surface of the energy and force distribution on the well components and well intervention tools at the end of the work string. We can now see, in real-time, what is happening downhole in well intervention operations.
The introduction of a new downhole digital technology has the potential to revolutionize well intervention operations through performance management, faster decision cycles and organizational change. The new system has the ability to send real-time downhole data from well intervention operations to the surface, and from there to data centers anywhere in the world. The system facilitates collaborative work by engaging a broader spectrum of specialists than has been traditionally available at the wellsite.A major benefit is the technology's capability as the catalyst for bringing about the significant organizational change required to replace currently aging offshore personnel with an adequate supply of competent employees within the context of the existing management and supply chain systems. Case studies are presented taken from over 20 field runs conducted during field integration testing.
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