The post COVID-19 era will undoubtedly present paradigm shifts in operational planning and execution and advanced automation will become an important factor. However, drilling automation without directional drilling (Cayeux 2020) capability will exclude the use of automation in a vast number of fields where precise placement of the wellbore has shifted from a luxury to a necessity. This is important in unconventional plays where automation can make a step change in operational outcomes (Chmela 2020). However, most efforts in automating directional drilling are using bespoke rigs (Slagmulder 2016) and bespoke bottom hole assembly (BHA) that limit operational options. The goal is in designing systems that enable directional drilling automation (Chatar 2018) with existing BHAs. This paper will look at three challenges that were identified and overcome to deploy a vendor agnostic system for automating the directional drilling (DD) process. The three challenges identified here are as follows:Using any mud motor including low-cost motors in a closed loopIntegration with an existing measurement and logging while drilling (MLWD) systemAbility to roll out automation systems on any operations with existing rigs The system is a modification of an operator’s autonomous drilling system (Rassenfoss 2011), designed to use existing rigs, BHAs and have minimum footprint on the rigs for operational use. The system will have a dedicated connection to the rig’s programmable logic controller (PLC) via common industrial protocols including Modbus, EthernetIP or Profinet, a physical connection the MLWD receiver and a brain box with a cloud connection to aggregate, process data and send commands to the rig PLC to execute directional commands. A vendor agnostic system will increase adoption of automated technologies and further drive improvements in operational and business performance.
In recent years digitalization has become one of the fastest growing disciplines in the oil and gas industry. Digital solutions reduce project costs, improve personnel and process safety. However, underestimation of the deployment complexity can also bring severe damage to the project execution, unnecessary delays, and ramp-up costs. To minimize negative effects and smoothen delivery process digital twins provide for oil and gas the opportunity to create a digital representation of the equipment, processes, and people behavior. Drilling is a very capital-intensive part of the oil and gas industry. It usessophisticated heavy machineries and typical rig contains various equipment from different vendors.Moreover, drilling process by itself has a lot of uncertainties and depends on human behaviors. Thismix makes most service and operating companies very cautious in introducing new technologies.Therefore, any solutions that can smoothen delivery process and minimize or even avoid any hitchesduring deployment bring a lot of benefits to the industry. Digital twin methodology is an ideal way toaccelerate new technologies deployment through offline full-scale digital testing. The paper highlights efforts to assist operators and drillingcontractors to create a methodology to optimize usage of their assets and improve their processes, using a combination of Systems Architype model and Systems Development lifecycle (SDLC), both well-established methodologies for systems development. Thefocus is on performance improvement, non-productive time reduction, oil and gas productionmaximization. Through emulating rig equipment, drilling process and personnel behavior it is possible toidentify the most critical parameters which guarantee reaching technical limits. Application of digital twin isan iterative process and typically includes several steps. Starting with setting targets, like negative impactreduction of the drilling process on subsequent production. Following by determination of the optimaldrilling parameters based on either historical or modelled data both from drilling and production. Theseparameters are the basis for the new drilling methodology. All deviations from existing drillingmethodologies and generic programs must be carefully analyzed and implemented. Finally drillingmethodology built using digital twin is ready for implementation in real world. The received data is goingto the next iteration to improve the methodology. This approach allows us to train personnel for field specificsituations without risking expensive mistakes in the real world.
During the past decade, drilling automation systems have been an attractive target for a lot of operating and drilling companies. Despite progress in automation in various industries, like mining and downstream, the drilling industry has lagged far behind in the real application of autonomous technologies implementation. This can be attributed to harsh environment, high level of uncertainty in input data, and that majority of stock is legacy drilling rigs, resulting in capital intensive implementations. In the past years there have been several attempts to create fully automated rigs, that includes surface automation and drilling automation. Such solutions are very attractive, because they allow people to move out of hazardous zones and, at the same time, improve performance. However, the main deficiency of such an approach is the very high capital investment required for development of highly bespoke rigs (Slagmulder 2016). And in the current business environment, with high volatility in oil and gas prices, plus the huge negative effect of the Covid-19 crisis on the world's economic situation, it would be hard to imagine that there are a lot of companies willing to make such a risky investment. In addition to this, due to the lack of demand, the market is full of relatively new, high-performance rigs. Taking all these into account, the obvious question is whether it makes sense to invest money and time into the development of drilling automation. The answer should be yes, for three substantial reasons:Automation improves personal safety, by moving people out of danger zones;Automation improves process safety, by transferring execution from person to machine, which reduces the risk of human error;Automation improves efficiency by bringing consistency to drilling and through the use of self-learning algorithms, which allow machines to drill each successive well better than the previous. This paper will not look into surface automation, such as pipe-handling, chemical and mud handling on site. The paper is focused on the subsurface, namely on the drilling automation process, the challenges that need to be overcome to deploy a vendor agnostic system on a majority of existing rigs. A vendor agnostic system is a modification of an operator's autonomous drilling system (Rassenfoss 2011), designed to use existing rigs, BHAs, and have minimum footprint on the rigs for operational use. A vendor agnostic system will increase adoption of automated technologies and further drive improvements in operational and business performance
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