Maintaining drillstring integrity is one of the main factors in a successful drilling operation. Drillstring integrity failure due to drillpipe fatigue remains to be a major problem. Drillpipe fatigue is caused by cyclic loading of bending (due to dogleg, sagging effect, buckling, and vibration) under rotation, which can lead to pipe twistoff. Collar or pipe off costs the operator millions of dollars to recover due to the cost of nonproductive times, fishing services, cement plugs, sidetracks, bottomhole assembly (BHA) lost in hole, and tool replacements. This failure can cause a significant impact to well cost. For preventive measures, the drilling industry still relies on regular drillstring inspection using nondestructive tests (NDT) to find drillpipe cracks before they grow and the pipe completely twists off downhole or at the minimum, limits the drillstring component's usable time based on the local experience. Until now, there has not been any sensor or method available to monitor the fatigue level of the components. Hence, the industry has a real need for a new method to manage drillstring integrity. Fatigue calculation is a well-established concept and applied in many industries, but not yet fully used to manage drillstring integrity. Several recent digital technology advancements now allow us to implement a fatigue management workflow. Using finite element modeling allows for simulating a fatigue test of connections and portholes in the collar and generates a list of fatigue properties for drillstring components. This method eliminates the expensive and time-consuming fatigue material test. Then, using an integrated dynamic design and analysis platform, allows for simulating the drilling process and calculating the expected loads along the drillstring during the drilling operation. By combining both capabilities in a well planning application makes it possible to calculate expected fatigue life consumed automatically for every designed BHA, which can be connected to an inventory system to select the optimum drillstring components having sufficient fatigue life for the job of interest. When implementing the application, a fatigue life monitoring workflow is also implemented that allows the engineer to monitor fatigue life consumption and take necessary action when it approaches the safety limit. Several technical solutions are required to implement this monitoring workflow, including improving computation speed with the modeling calculation on the cloud and high-performance computing parallel computations, leveraging bending load data from downhole bending sensors to validate and calibrate the modeling, and evaluating historical performance in the maintenance database to continuously refine the workflow. This innovative workflow has been implemented to manage BHA integrity for medium-to-high dogleg severity (DLS). The approaches in managing fatigue life enable risk mitigation for BHA integrity, push kickoffs deeper, shorten the curved sections, and increase reservoir exposure, including reentry applications. This paper presents some field examples that demonstrate how this solution provides drilling operations with a new tool to reduce fatigue failures by predicting expected fatigue life consumed on a job, selecting correct tools, and proactively managing the drilling risks.
Over the years, considerable research has been conducted and the results of numerous studies have been published about optimizing drilling operations that maximize the footage drilled and minimize drilling costs. One of the optimization aspects studied is determining which drilling parameters improve drilling efficiency. Many drilling application software packages exist to help engineers simulate the drilling process. These software packages might include the capability to evaluate drilling parameters’ sensitivity; however, many of the software programs only focus on a specific engineering area and rely on the engineer to evaluate the relation between the results of an engineering analysis and deciding. A new approach has been developed that consolidates various engineering analyses into a single workflow to automatically define the optimum drilling parameters. The application provides a drilling parameters roadmap consisting of weight on bit (WOB), surface rpm, and flow rate for efficient drilling execution. This application uses the knowledge of offset wells as a starting point to define the WOB and RPM ranges. Those values are represented as a drilling parameter matrix for input into the model. Then, by using static and dynamic bottomhole assembly (BHA) modeling and hydraulics modeling in addition to predicted rate of penetration (ROP), the application runs various sensitivity analyses to obtain the optimum drilling parameters within rig and downhole equipment specifications. The sensitivity analysis with static BHA modeling provides the buckling check to the maximum WOB proposed while the dynamic BHA modeling provides downhole vibration analysis and predicts the drilling ROP, which is compared with downhole tool specifications. Then, the hydraulic modeling provides validation of hole-cleaning quality for the relation between flow rate and ROP, without exceeding rig pump and circulating system pressure specifications. The application also implements a smart learning process to reduce the number of iterations and computation time. The results of this approach were tested on a field project where implementing the roadmap computed from the application showed excellent results for improving drilling performance.
Application of Rotary Steerable System(RSS) drilling in one of the biggest Indian offshore field , Mumbai High was driven by the increasing difficulties associated with directional drilling by mud motor technology, especially in Extended Reach wells. ONGC has focused largely on finding economic and competitive ways of exploiting the mature and depleted field. Rotary Steerable System provides the opportunity to reach farthest unexploited subsurface targets without adding new platforms with significant improvement in drilling performance and challenging subsurface objectives. Since first application in the year 2004, RSS has successfully overcome the drilling challenges & problems, especially in 12¼"section, deliver improvement in drilling time. The paper will discuss in detail, each step of continuous improvement in RSS applications & operations, field specific bit design, drill string , fluid system modifications and real time drilling optimization during the last seven years. The actual result on overall directional drilling efficiency enhancement after implementation of each optimization methodology is also discussed. The discussion covers some unique RSS applications in Mumbai High Fields such as:, drilling top hole 17-1/2" section to complete the well in required hole size, drilling 8-1/2" multilateral section including open hole sidetrack, drilling 6" with RSS & pro-active geo-steering technologies keeping the well in good reservoir with high penetration rate and long horizontal drift. Based on the field results and performance analysis it is concluded that continuous up gradation of mud system, bit design, string design and real time monitoring with proven technology of RSS lead to successful completion of high drift wells.
Our industry continues drilling more challenging wells - deeper and higher dogleg severity (DLS). Bottom Hole Assemblies (BHAs) have also become more complex and required to sustain higher loads. The current design and engineering practices still rely on prevention mechanical overload which based on calculated maximum stress versus component material yield strength. While fatigue failure is well known and recognized as the primary cause of component twist-offs downhole, but there still limited approach to prevent it during planning phases such as BHA design, execution monitoring, and evaluation. The industry still relies on inspection and traditional cumulative pumping hours tracking as a preventive action against fatigue failure. Fatigue damage consists of two stages, crack initiation and crack propagation, with crack initiation accounting for most of the total life. Rotating bending is the driving force for fatigue cracking. It induces cyclic stresses and strains at the stress risers, which are the fatigue-critical features. Fatigue data can be presented in the form of S-N curves, where S is the applied bending stress and N is the total life in a number of cycles. An advancement in BHA modeling with the capability of finer detailed finite element modeling of drilling tool component allows for accurate calculation of BHA bending moment distribution. Given a bending moment, the cyclic stresses and strains at the most critical feature of the most critical BHA component can be determined. The life of the most critical component can then be calculated with the stress-life or strain-life curve of the collar material. This governs the life of the entire BHA. This paper will present the development of new approach on fatigue management workflow which includes bending moment & stress analysis based BHA design, fatigue life prediction and sensitivity analysis during planning and execution monitoring on consumed fatigue life, including job tracking to component maintenance system. The paper will also discuss the accelerated cumulative fatigue due to shock & vibration. A fatigue management workflow has been created for planning, execution monitoring, and post-job evaluation phases. During planning, the engineer can calculate the expected fatigue life of the BHA and optimize for the expected duration of the job. The result can be used to select reliable components with sufficient fatigue life for the job. While drilling, this method enables the engineer to continuously monitor the consumed fatigue life of any BHA component and make the decision to replace the tool before a failure occurs downhole. After the job, the consumed life can be recorded in the maintenance system to track the remaining life and decide what preventive maintenance is required. The new modeling approach enables the drilling engineer to optimize performance and managing BHA integrity risk.
Drilling wells with minimum risk and optimizing well placement with the least possible cost are key goals that companies strive to achieve. The major contributor to the successful execution of the well is the quality of the drilling program. Well design is a complex process, which requires full collaboration of multiple domain roles & expertise working together to integrate various well-planning data. Many design challenges will be encountered, such as risk assessments, domain-specific workflows, geological concerns, technology selections, cost & time estimation, environmental and safety concerns. Design process efficiency depends on effective communication between parties, quickly adapting to any changes, reducing the number of changes, and reducing complicated & manual processes. Current existing workflow and tools are not promoting an excellent collaborative environment among the different roles involved. Engineers utilize multiple engineering applications, which involved many manual data transfers and inputs. The different party is still working in a silo and sharing the design via email or other manual data transfer. Any changes to the design cause manual rework, leading to inconsistency, incoherency, slow decision & optimization process, and failure to identify all potential risks, increasing the well planning time. The new digital planning solution based on cloud technology allows the design team to maximize the results by giving them access to all the data and science they need in a single, standard system. It's a radical new way of working that gives engineers quicker and better-quality drilling programs by automating repetitive tasks and validation workflows to ensure the entire plan is coherent. This new planning solution allows multiple roles & domain collaboration to break down silos, increase team productivity through tasks assignment, and share all data. An automated trajectory design changes the way engineers design trajectory from manually connecting the path from a surface location to the target reservoir location to automatically calculate & propose multiple options with various KPIs allowing the engineer to select the best trajectory option. The system reinforces drilling program quality through auto engineering analysis, which provides quick feedback for any design changes and provides an integrated workflow from the trajectory design to operational activity planning and AFE. The automation of repetitive tasks, such as multiple manual inputs, frees domain experts to have more time to focus on creating new engineering insights while still maintaining design traceability to review updates over the life of the projects and see how the design changes have optimized the drilling program. This new solution solves some of the significant challenges in the current well-planning workflow.
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