In this paper we present a new type of vibration related to PDC bits in drilling and its mitigation: a vibration coupled in axial, lateral and torsional directions at a high common frequency (3D coupled vibration). The coupled frequency is as high as 400Hz. 3D coupled vibration is a new dysfunction in drilling operation. This type of vibration occurred more often than stick-slip vibration. Evidences reveal that the coupled frequency is an excitation frequency coming from the bottom hole pattern formed in bit/rock interaction. This excitation frequency and its higher order harmonics may excite axial resonance and/or torsional resonance of a BHA. The nature of 3D coupled vibration is more harmful than low frequency stick-slip vibration and high frequency torsional oscillation (HFTO). The correlation between the occurrence of 3D coupled vibration and bit design characteristics is studied. Being different from prior publications, we found the excitation frequency is dependent on bit design and the occurrence of 3D coupled vibration is correlated with bit design characteristics. New design guidlines have been proposed to reduce or to mitigate 3D coupled vibration.

One unique facet of digital technology is the merging of separate technologies for new workflows and products. Like other industries, energy is also doing this. This project will automate the bit inspection process and this system will reduce labor costs, increase product quality, and improve bit performance. The innovation center is working on various aspects of the project, which aims to join automation technologies with robotic capabilities. Industrial robots are used extensively in traditional high-volume manufacturing applications. The high-mix, low-volume nature of oil and gas manufacturing operations has impeded deployment of automation solutions. Recent advances in sensors, computers, and machine learning now enable integrating robotics and automation technologies into these flexible manufacturing workflows. Driven by digital transformation, an automated inspection system for polycrystalline diamond compact (PDC) drill bits has been developed. The system uses high-resolution robotic 3D scanning, 2D imaging, and artificial intelligence to improve inspection efficiency and product quality. In our user-experience- (UX-) focused approach, we streamlined the user interface (UI) research methods to develop the robotic inspection UI and successfully tested the design with end users. This paper introduces the inspection system and improved workflows for the PDC bits, illustrates the innovative UX/UI development process, and targeted evaluation with the end users, which is crucial before deploying the system in production. We also concluded with some recommended improvements to guide future work.

Although visual data analytics using image processing is one of the most growing research areas today and is largely applied in many fields, it is not fully utilized in the petroleum industry. This study is inspired by medical image segmentation in detecting tumor cells. This paper uses a supervised Machine Learning technique through video analytics to identify bit dullness that can be used in the drilling industry in place of the subjective screening approach. The evaluation of bit performance can be affected by subjective evaluation of the degree of dullness. The present approach of using video analytics is able to grade bit dullness to avoid user subjectivity. The approach involves the use of datasets in good quantity and quality by separating them into training datasets, testing datasets, and validation datasets. Due to the large datasets, Google Collaboratory was used as it provides access to its Graphic Processing Unit (GPU) online for the processing of the bit datasets. The processing time and resource consumption are minimized using Google GPU. Using the Google GPU resources, the procedure is automated without any installation. After the bit is pulled out and cleaned, a video is taken around and up and down in 360°. Further, it is compared against the green bit. By this approach, multiple video datasets are not required. The algorithm was validated with new sets of bit videos and the results were satisfactory. The identification of the dullness or otherwise of each screened bit is done with the aid of a bounding box with a stamp of a level of confidence (range 0.5–1) and the algorithm assigns for its decision on the identified or screened object. This method is also able to screen multiple bits stored in a single place. In an event where several drill bits are to be screened, manual grading will be a huge task and will require a lot of resources. This model and algorithm will take a few minutes to screen and provide grading for several bits while videos are passed through the algorithm. It has also been found that the grading with the video was much better than the single image as the contextual information extracted are much higher at the level of the entire video, per segment, per shot, and per frame. Also, methodology is made robust so that the video model test starts successfully without error. The time penalty for the processing is fast and it took less time for a single video screening. The work developed here is probably the first to handle the dull bit grading using video analytics. With more of these datasets available, the future automation of the IADC bit characterization will soon evolve into an automated process.

In a fast drilling environment, suchas shale drilling, refining advanced technologies for preventing downhole toolfailures is paramount. Challenges are still very much associated with complex bottom-hole assemblies and the vibration of the drill string when used with a downhole mud motor. The mud positive displacement motor with various lobe configurations and designs becomes an additional excitation source of vibration. Further, it affects the transient behavior of the performance mud motor. Unbalanced force exists because the center ofmass of the motor rotor does not coincide with the axis of rotation.Further, the vector of full acceleration of the center of the rotor can be decomposed into two perpendicular projections—tangent and normal—which aretaken into account and integrated intothe full drill string forced frequency modelas force and displacement at the motorlocation. The paper includes two models, first one to predict the critical speeds and the second one to see the transient behavior of the downhole parameters when the mud motor is used.The model also considers the effect of the stringspeed. The unbalanced force is more pronounced at the lower pair or lobe configuration as compared to the higher pairlobe configuration because of the larger eccentricity. The unbalance is modeled in terms of an equivalent mass of therotor with the eccentricity of the rotor. Also, the analysis provides an estimation of relative bending stresses, shear forces, lateral displacements and transient bit rpm, bit torque, and weightone bit for the assembly used. Based onthe study, severe vibrations causing potentially damaging operating conditionswhen transient downhole forcing parametersare used for the vibration model.It has been found that when a mud motor isused using static forcing parameters may not provide the conservative estimation of the critical speeds as opposed totransient parameters. This is because coupled oscillations fundamentally can create new dynamic phenomena, which cannot be predicted from the characteristics of isolated elements of the drilling system.

This paper reviews field data where high-frequency torsional oscillation (HFTO) was seen on previous bit runs and hypothesizes on features or design metrics that may have directly influenced this vibration. This paper investigates four metrics of bit design: Cutter wear, shear length:shear area ratio, choice of secondary cutter material, and effective backrake. Hypotheses are established linking these metrics to HFTO, and then data from field runs is shown to correlate the hypotheses. At this point, a bit was designed and manufactured to put the HFTO avoidance hypotheses into practice. Prior to laboratory testing, a theoretical model is used to identify resonant torsional frequencies. A series of laboratory experiments followed to test the hypotheses and demonstrated that there is correlation between all factors, but in one case is counter to the hypothesis. This information is of use when selecting or designing bits in environments where HFTO is known to occur. The findings may also assist in explaining performance that's below expectations where HFTO is not able to be explicitly measured.

It is useful during drilling operations to know when bit failure has occurred because this knowledge can be used to improve drilling performance and provides guidance on when to pull out of hole. This paper presents a simple polycrystalline diamond compact (PDC) bit wear indicator and an associated methodology to help quantify wear and failure using real-time surface sensor data and PDC dull images. The wear indicator is used to identify the point of failure, after which corresponding surface data and dull images can be used to infer the cause of failure. It links rotary speed (RPM) with rate of penetration (ROP) and weight-on-bit (WOB). The term incorporating RPM and ROP represents a "sliding distance", i.e. the number of revolutions required to drill a unit distance of formation, while the WOB represents the formation hardness or contact pressure applied by the formation. This PDC bit wear metric was applied and validated on a data set comprised of 51 lateral production hole bit runs on 9 wells. Surface electric drilling recorder (EDR) data alongside bit dull photos were used to interpret the relationship between the wear metric and observed PDC wear. All runs were in the same extremely hard (estimated 35 – 50 kpsi unconfined compressive strength) and abrasive shale formation. Sliding drilling time and off-bottom time were filtered from the data, and the median wear metric value for each stand was calculated versus measured hole depth while in rotary mode. The initial point in time when the bit fails was found to be most often a singular event, after which ROP never recovered. Once damaged, subsequent catastrophic bit failure generally occurred within drilling 1-2 stands. The rapid bit failure observed was attributed to the increased thermal loads seen at the wear flat of the PDC cutter, which accelerate diamond degradation. The wear metric more accurately identifies the point in time (stand being drilled) of failure than the ROP value by itself. Review of post-run PDC photos show that the final recorded wear metric value can be related to the observed severity of the PDC damage. This information was used to determine a pull criterion to reduce pulling bits that are damaged beyond repair (DBR) and reduce time spent beyond the effective end of life. Pulling bits before DBR status is reached and replacing them increases overall drilling performance. The presented wear metric is simple and cost-effective to implement, which is important to lower-cost land wells, and requires only real-time surface sensor data. It enables a targeted approach to analyzing PDC bit wear, optimizing drilling performance and establishing effective bit pull criteria.

An operator, drilling a 6-in horizontal production section in an offshore African field, observed diverging directional drilling steering behaviour that resulted in a round trip non-productive time (NPT) event. Being a mature field of known drilling performance and no significant structural or lithological variations, the interval was planned for one run with a Rotary-Steerable-System (RSS) bottom hole assembly (BHA). During the horizontal drilling of a particular well, the BHA began to build inclination, and all attempts to correct trajectory resulted in incremental build. Initial root cause indications were a malfunction in the RSS due to opposite steering behaviour and not a geological explanation. To complete the remaining drilling interval, the drill bit design was changed and the steering unit replaced with standby inventory. Drilling was resumed and the horizontal geosteering interval was completed with responsive directional control to the downlinked commands through the same reservoir geology. Extensive root cause analysis that combined in-depth bit and BHA modelling, physical RSS tool workshop testing, and detailed plotting of all surface and downhole data, verified possible malfunctions and identified potential negative steering behaviour. Proprietary digital simulation tools modelled the BHA bending behaviour and build up rates. Simulations of bit-BHA interactions in formation scenarios were run to define build and/or drop capabilities. Different drill bit designs were evaluated through the modelling iteration process to understand the observed field responses. Inspection and physical tool testing confirmed that the RSS tool was fully operational without any issues. Modelling matched the actual field outcomes in which drill bit features contributed to the observed lack of steering responsiveness, delivering drilling in a direction opposite to downlinked commands. An extended gage length bit drilled a 3.3deg/100ft build up rate, with an average 93% downward steer force, when a drop rate of 6.0deg/100ft was expected. Applying the new drill bit design with key gage features corrected the well trajectory with a 65% reduction in steering force. After 0.45hours of directional corrections, subsequent drilling kept precise target inclination enabling a 56% rate of penetration (ROP) improvement compared to the first run. Quality wellbore placement and NPT risk reduction can be achieved by utilizing proven and state-of-the-art digital simulations that combine bit with BHA and formation during the pre-planning phase to ensure appropriate drill bit designs are harmonized to the BHA and directional requirements. This paper illustrates the benefits when applying and adverse risk when not applying an integrated systems approach.

Longer lateral length in unconventional wells has proven to increase hydrocarbon recovery and lower overall development costs for oil and gas operators in North America. The application of rotary steerable system (RSS) technology aids this effort by improving and sustaining penetration rates to reduce well time and maximize reservoir drainage. A new "intelligent" RSS has been deployed to enhance drilling efficiency with industry-leading operating limits, automated steering controls, and a global lifecycle maintenance system to drive reliability. The new RSS bottomhole assembly (BHA) consists of an advanced downhole motor, a matched bit design, and high-speed geosteering control. An automation process helps operators meet the challenges of drilling time and wellbore placement in long laterals. High rate of penetration (ROP), rotation per minute (RPM) and weight on bit (WOB) limits are controlled by sophisticated sensor technology that enables precise steerability. The RSS platform includes multiple directional sensors and real-time processors capable of reducing hole tortuosity and optimizing reservoir exposure while drilling. It also includes automated inclination and azimuth control features. Furthermore, a structured, pre-job design process evaluates critical engineering risks and mitigates those risks using a systematic methodology. The initial testing of the new RSS on a test beam qualified its ability to operate at high speeds and high loads. Multiple holes were drilled in cement blocks to benchmark performance. Beam testing was followed by full-scale testing at a dedicated drilling rig, where over 40,000 ft was drilled in a variety of configurations, including vertical, curve, and lateral trajectories. After the extensive field testing program, the intelligent RSS was utilized to drill multiple ~14,000-ft, 8.5-in. lateral hole sections in the Utica Shale. A significant reduction of drilling time was achieved in these long laterals, with an average ROP of 245 ft/hr. A record 5,300 ft were drilled in 24 hours, beating previous wells by 600 ft. The activation of inclination and azimuth control delivered a smooth, high-quality wellbore with minimal tortuosity. Inclination was maintained within +/− 0.5° and azimuth +/− 1°. The outstanding performance of the innovative BHA enabled the longest one-run lateral to be drilled with an RSS. The new, intelligent RSS has successfully demonstrated it can decrease well time and drilling costs, while increasing wellbore placement accuracy. The improvement in drilling efficiency and lateral length capability will enhance unconventional asset value across North America, and elsewhere around the world.

During the last decade, a tremendous amount of work has been published on using surface measurement of mechanical specific energy (MSE) for enhancing drilling efficiency and maximizing rate of penetration (ROP). With an increase in directional drilling, surface measurement of MSE doesn't correlate with downhole conditions due to frictional losses along the drill string and bottom hole assembly (BHA). Attempts to measure weight on bit (WOB) and torque on bit (TOB) downhole typically involve expensive tools that are deployed 50-100 feet behind the bit. The authors present a novel in-bit strain sensor that measures WOB and TOB in the bit while drilling. This new approach is completely non-invasive and does not change the BHA. Field testing has shown that in many circumstances only 50% of the surface indicated weight reaches the bit and drilling performance suffers including low ROP and higher vibration levels. This highlights the importance of managing the directional plan and using methods to improve weight transfer. This new in-bit measurement tool has been used to drill over 100,000ft in applications around the world and provides useful insights into drilling performance.

Wells in the Permian Basin continue to increase in technical complexity and lateral length, testing the limits of traditional completion practices in unconventional wells. Coiled tubing has been the standard method for drilling out frac plugs in the basin but has mechanical limitations in extended-reach and high-pressure laterals. Due to the increasing well complexity operators have begun using high technology hydraulic completion units (HCU), also known as a snubbing unit, to drill out frac plugs in certain Permian Basin wells. By using the HCU in wells with longer laterals, higher pressures, and downhole uncertainty/complexity some of the additional risk can be mitigated. The HCU system can provide a reliable and cost-effective means to cleanout laterals in the Permian Basin while reducing mechanical risk. The purpose of this paper is to present case histories that illustrate the positive impact of the HCU on field operations. This paper will also detail the evolution of the HCU over time to its current state of the art stand-alone rigless system.

There are many challenges to be overcome when drilling lateral sections in the Wolfcamp horizon of the Delaware Basin. These include wellbore instability, formation heterogeneity, low rate of penetration (ROP), poor weight transfer and drill bit damage. Downhole data was captured in order to provide insight into these challenges. A Downhole Dynamics Tool (DDT) was used to capture the data necessary to investigate the drilling performance challenges. The data collected was downhole weight on bit (DHWOB) and torque, downhole bending moments and tool face, annular and bore pressure readings, and downhole vibrations. The analysis of these data provided insights into the effectiveness of connection and WOB zeroing practices, clarity about recurrent bit nozzle plugging and bit damage, and a better understanding of wellbore tortuosity and effective WOB transfer. The DDT was used on multiple wells, in memory mode and in real-time. On the initial trial well, the tool was run in memory-only mode due to drilling system requirements; subsequently real-time data was additionally used to further optimize drilling performance. After retrieving the data and analyzing trends from the initial memory-only runs, the following could be highlighted: Using downhole pressure and WOB, it was shown that the bit was still on-bottom during connections. Pipe stretch calculations were performed and matched with downhole data in order to verify minimum stick up length required to effectively pick the bit off-bottom during connections. This allowed the development and adoption of a new standard for connection practices. The downhole bending moment data identified the presence of wellbore rugosity driven by several factors, including magnitude of the steering force from the rotary steerable system (RSS) steering unit. Downhole WOB data showed that weight transfer efficiency was not 100%. The loss of WOB is inferred to be caused by factors such as hole rugosity, inconsistently zeroed surface WOB and friction losses. The data obtained about the causes of bit plugging, bit coring damage, and wellbore rugosity, was used to redesign and optimize future bits to be used in lateral drilling operations. Some of the recommended enhancements included changes in nozzle orientation, improved impact resistance for inner cutting structure and improved gauge pad design. Use of downhole data identified factors affecting drilling performance which differed from what was initially believed. The use of downhole data enabled changes in operational practices, drill string and bottom hole assembly (BHA) design, bit design, and drilling parameter roadmaps. The lessons learned and best practices from the data analysis were successfully transferred and implemented across all development areas in the Permian Basin.

IADC dull bit grading is the current industry standard to assess the condition of a drill bit when it comes out of the hole. It is intended to capture the impact of drilling issues (e.g. drilling abrasive hard rock, drilling dysfunctions) on the bit and to improve future bit selection. However, the grading process is manual and subjective, making the bit grading outcome an inconsistent and unreliable metric. Recent advances in image processing and deep learning allow for bit grading to become more consistent and automated. Such a process is described in this paper. The dataset used in this project consisted of multiple images (taken from different perspectives in a random manner) of used drill bits from 13 bit runs across multiple wells. As a preliminary step in developing the approach, only PDC bits were considered in this project. The first task was to identify all the cutters on a drill bit image using Convolutional Neural Networks (CNN). The CNN approach was chosen since it has shown remarkable success in solving the problem of object detection and classification in other fields. Next, the amount of damage to each cutter was quantified using image processing techniques. Finally, from information gathered in the previous steps, a holistic damage assessment of the drill bit was made. The trained CNN was able to detect the cutters in an image to a high degree of accuracy. The accuracy of cutter detection was further improved through the use of heuristics that predict potential locations of cutters based on blade location and shape. The identification of unique cutters from a group of images of the same bit proved more challenging. Since the images could not be appropriately stitched together, each image was graded independently, and a holistic assessment of the bit was made by aggregation of the individual assessments. Additionally, not all of the cutters identified could be positively identified as damaged or not. For example, if the perspective that was available was at a right angle to the cutter's face, it is inherently not possible to quantify the damage. The computer-generated assessment of the bit was validated with collaborative assessments made by multiple human operators. This paper presents a novel approach to bit damage classification that removes the subjective bias that comes with human evaluations. The application of deep learning techniques to cutter identification, damage detection and quantification is unique and has the potential to significantly improve bit design, selection, and thus, drilling efficiency.

A West Texas operator historically used four to seven PDC bits to TD their Ward County, Wolfcamp B laterals. Formations there are lithologically more challenging when compared to the same interval in adjacent Reeves County. Drilling performance in Reeves County Wolfcamp A laterals averages approximately 1,091 Feet/Day while those in Ward County seldom make 600 Feet/Day. Often daily progress is less than that. The objective was to improve Ward County lateral drilling performance. In the study presented here, we examined the BHAs, bits and motors in consecutive Wolfcamp B laterals on the same pad which used 7 and 5 bits to reach TD respectively. Several of these PDC bits were Damaged Beyond Repair (DBR) as illustrated later. We demonstrate the process of utilizing Time Domain Analyses (TDA) as an accurate method to identify and analyze the nonlinear, dynamic behavior of drilling systems. These enhanced models allow the engineer to explore a full range of alternative BHA responses based upon current drilling conditions. They account for most of the specific details of downhole equipment such as the bit, the rotary steerable systems (RSS) or steerable mud motor, the MWD and their interaction with the hole. The software used allows virtual sensors to be placed anywhere along the drill string to evaluate the dynamics for additional insights.

Maximizing stimulated natural and hydraulic fracture network is one of the primary hydraulic fracturing concerns for economic production from a horizontal shale gas well. Geomechanical facies and preexisting fractures in each stage are identified based on similarities in formation characteristics to optimize the locations of perforation clusters. This often requires analyzing large volumes of drilling, Logging While Drilling (LWD) and Measurement While Drilling (MWD) data. In this paper, we develop a methodology that calculates the mechanical specific energy (MSE) using real-time drill string acceleration signals directly from its definition. High resolution vibration signals have been collected using a tri-axial accerlometer, which was an auxiliary tool included in acoustic borehole imager. This technique provides a cost-efficient solution for engineered completion design. Furthermore, we adopt deep Convolutional Neural Network (CNN) with signal processing to build a data pipeline that effectively extracts patterns from dynamic acceleration signals for rock lateral MSE classification. First, we apply discrete wavelet transform and Short-Time Fourier Transform (STFT) for signal denoising and pattern recognition. Then we construct an image dataset using multi-scale image fusion at pixel level from 3 sensor channels, including axial, lateral acceleration spectrograms and zero-padded revolutions per minute (RPM). The resulted RGB image dataset includes 4,000 images of 5 MSE ranges with various rock strength conditions. Our results demonstrate that the proposed deep learning model can achieve more than 90% classification accuracy. The deep learning results, as a reference source, were applied in selected Marcellus Shale Energy and Environmental Lab (MSEEL) wells engineered completion located in the Marcellus shale gas site.

Operators face the continuing challenge to improve drilling efficiency for cost containment, especially in deepwater drilling environments where drilling costs are significantly higher. Innovative drilling technologies have been developed and implemented continuously to support the initiative. In many areas of the world, including the Gulf of Mexico (GOM), hydrocarbon reservoirs exist below thick non-porous and impermeable sequences of salt that are considered a perfect cap rock. However, salt poses varied levels of drilling challenges due to its unique mechanical properties. At ambient conditions, the unconfined compressive strength (UCS) of salt varies between 3,000 to 5,000 psi; however, the strain at failure for salt can be an order of magnitude higher when compared to other rocks. Consequently, during drilling salt's viscoelastic behavior requires that its must be broken with an inter-crystalline or trans-crystalline grain boundary breakage. When compared to other rock types, the unique isotropic nature of salt results in a level of strain that is much higher for the given elastic moduli. This strain level makes salt failure mechanics different from other rock types that are prevalent in the GOM. Hybrid bits combine roller-cone and polycrystalline diamond compact (PDC) cutting elements to perform a simultaneous on-bottom crushing / gouging and shearing action. Two divergent cutting mechanics pre-stresses the rock and apply high strain for deformation and displacement, resulting in highly efficient cutting mechanics. To meet the drilling objectives, different hybrid designs have been implemented to combine stability and aggressiveness for improved drilling efficiency. An operator, while drilling salt sections at record penetration rates, has successfully used this innovative process of rock failure utilizing the dual-cutting mechanics of hybrid bits. This has resulted in significant value additions for the operator. This paper analyzes field-drilling data from successful GOM wells and attempts to correlate salt failure mechanics and provide insight into dual-cutting mechanics and its correlation with salt failure. The paper also reviews the drilling mechanics of hybrid bits in salt and highlights importance of dual-cutting mechanics for achieving higher penetration rates in salt through improved drilling efficiency.

Mechanical specific energy (MSE) has been widely used in the industry to monitor drilling efficiency. However, it does not give detailed information about energy flow in the drilling system and lacks the resolution to identify the root cause of energy loss. The drilling operation is a dynamic process. Energy input may be from a surface-drive system (top drive or rotary table) or a mud motor placed downhole. In a perfect world, all of the energy is used to drill the rock. However, some of the input energy may reside in the drillstring as strain and kinetic energy due to the deformation and motion of the drillstring. Drilling energy is dissipated due to shock, vibration, fluid damping, and frictional contact between the drillstring and wellbore. A novel method has been developed to calculate the drilling energy flow in the drillstring and to enable better drilling energy management by maximizing useful energy consumption and reducing energy waste. The method provides a new way to understand and improve drilling efficiency. The method is based on an advanced transient drilling dynamics model which simulates the full drilling system from surface to bit. The entire drillstring is meshed using 3D beam elements, and its dynamic response history is solved by the finite element method (FEM). The energy input can be calculated from surface drilling parameters, such as torque, rotation speed, flow rate, and motor differential pressure. With the simulated history of forces and dynamics of the drillstring, the corresponding strain energy and kinetic energy of the drillstring can be evaluated. The detailed cutting structure model can provide insight on the energy amount consumed by the rock cutting action of the bit and reamer. Putting all the components together leads to a holistic calculation workflow of drilling energy. Field case studies were conducted to examine the effectiveness of this method. The studies showed the drillstring strain energy and kinetic energy are good performance indicators for drillstring reliability and stability because these energy variables reflect the severity of loading and vibration in the drillstring. The energy variables possess clear signatures for interpretation of different downhole vibration modes. Currently, the drilling efficiency is normally evaluated by MSE, which represents the amount of energy needed to remove a unit volume of rock using the surface drilling data. In this study, the energy loss is calculated to understand the percentage of input energy dissipated due to the interaction of the drillstring with the environment. In contrast to MSE, the calculation provides a more direct and detailed measurement of drilling efficiency. It gives a methodology for understanding detailed energy flow in the drilling system under different drilling vibration modes. It can be applied to bit selection, bottomhole assembly (BHA) design, and drilling parameter optimization to achieve better drilling energy management and improve drilling efficiency. The novel approach calculates drilling energy based on the transient dynamics simulation of the full drilling system. It provides a detailed and holistic view of drilling energy input, propagation, and consumption. This method could help identify the inefficient drilling conditions and optimize drilling operation through evaluating and comparing different options.

After findings were made in the pre-salt province that represented a major discovery for the oil industry, drilling activity in Brazil has been focused primarily on economically viable ways to develop these reserves. The pre-salt cluster is a geological formation that consists of organic microbial carbonates and other sediments. The reservoir poses innumerous drilling challenges, including hard silicate nodules and low-porosity layers, which make the formation strength extremely high. Also, the heterogeneity level of such carbonates (within centimeters) imposes extra challenges, especially on drilling shock & vibration, with low rates-of-penetration (ROP), raising pre-salt well construction costs. To offer a technical solution, the service provider applied an innovative approach based on two pillars: a model-based design approach, leading to two drill bit designs with improved cutting structure resistance, with dynamic stability, delivering the entire section in one bit run with higher ROP. Along with the technology, a new workflow called "stratigraphic zonation for drilling" was implemented. This paper reviews the work covering this new stratigraphic zonation workflow, the development of this virtual drilling scenario and some field results with lessons learned and way forward.

Torsional instability in a drilling system is a significant challenge that limits performance. In its extreme form, known as stick-slip, the drillstring stops and restarts, exposing its downhole equipment to extreme forces that can lead to failures, unintended trips, and escalated operation costs. Torsional instability can also trigger lateral dysfunctions and whirl, creating further risk of bit and bottomhole assembly (BHA) failure. The risk of torsional dysfunction is heightened in applications involving concentric reamers and long drillstring, high-angle wells. The correlation of polycrystalline diamond compact (PDC) bits with torsional dysfunction is well known, and different approaches have been suggested to address the issue. The fixed depth of cut control (DOCC) approach, which is commonly used to address the issue, limits the PDC bit and formation engagement at a pre-determined ratio of rate of penetration (ROP) and drillstring RPM. However, this approach has an uncertain success rate when drilling conditions change. To address the challenge of torsional dysfunction while drilling a directional well with a 12¼-in. pilot bit and a 14½-in. concentric reamer, a self-adaptive DOCC technology was deployed in a deepwater well in the Gulf of Mexico (GOM). The self-adaptive DOCC technology automatically adjusts the depth of cut engagement threshold as drilling conditions change, eliminating the manual parameter adjustment required at surface to manage torsional dysfunction. The application of self-adaptive drill bit technology in the target well yielded excellent results, and the section was completed with a single bit/BHA run. Ninety-eight percent of the interval was drilled with no torsional dysfunction. The drillstring whirl was negligible, and 99% of the interval was drilled without lateral vibration. Eliminating harmful dynamic dysfunction significantly enhanced drilling performance and increased the ROP by 57% over the best PDC offset run. The dull bit condition was very encouraging; the bit displayed very low wear and no undesired impact damage, showing the effectiveness of the technology. This paper uses real-time drilling dynamics field data measured downhole and demonstrates the effectiveness of self-adaptive DOCC technology for drilling performance improvement in deepwater directional well where torsional dysfunction continues to remain a significant challenge and could be a performance limiter.

History of Underreamer Blocks and Problem Description Conical Diamond Elements in Underreamer Blocks Complementary Design Features 4D Simulation Software Introduction 4D Simulation and Design Approach Vibration and Drilling Efficiency Lab Testing 18.125-in × 22-in HEWD Job and 4D Simulation Study 12.25-in × 14.75-in URO Job 8.5-in × 9.0-in HEWD Job Conclusion

Previously published technology that was not used in a company was implemented using a new approach based on marketing technology that resulted in widespread adoption and a lasting change. The drilling technology was available for years in SPE papers. Previous attempts to implement it failed to establish lasting application. The initiative took about two years and resulted in the use of the technology being well established. In addition to the process used to implement the initiative, the drilling technical process is also summarized. The initiative drove implementation of the use mechanical specific energy (MSE) and other techniques to identify and minimize bit dysfunction and bit and bottomhole assembly vibrations. Full implementation of the techniques required drilling managers, superintendents, and engineers in the office, company drill site managers on rigs, and drilling contractor and service company personnel both on site and in the office all to understand the value of the technology, as well as know how to apply it. The implementation process included an initial awareness phase of sharing successes by early adopters to create demand for the technology. Implementation included comprehensive training, management support, technical tools, and ongoing support. The result of the initiative was a dramatic improvement in drilling performance. Significant increases in rates of penetration were achieved with virtually no added operational cost. Good results have been obtained in all business units, and the processes have evolved into routine practices. The key conclusion is that proven marketing techniques can be adapted and applied to internal initiatives. The technology of marketing is effective and available, but adapting it to use internally is not trivial or obvious. On some previous initiatives, the approach was to deliver the technology, then create demand for it. The technique used this time was to create the demand first, then deliver the technology. This approach was successful in reducing opposition. Early adopters must be identified and supported. Their initial successes are used to create demand for the technology and willingness to participate in training and learning. Training must be delivered to all of the people involved to enable application of the new process or technology. Management support and technical support are both essential to get past difficulties. Patience and understanding are the best techniques to deal with resistance. Ultimately, successful results are the key to full adoption, but successful results cannot be achieved without the previous steps. This case history includes both the principles and the application to a real case, with enough information on the drilling technology to understand the marketing process. The novel and additive information is how to adapt marketing technology for internal use, which is important for companies to adopt new technology faster.