Bottom Hole Assembly Research Articles

Machine-Learning Approach PredictsGel Strength of Drilling Fluid While Drilling

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 35433, “Novel Machine-Learning Approach for Predicting the Gel Strength of the Drilling Fluid While Drilling,” by Ahmed Gowida, SPE, and Salaheldin Elkatatny, SPE, King Fahd University of Petroleum and Minerals. The paper has not been peer reviewed. Copyright 2024 Offshore Technology Conference. _ Accurately estimating gel strength is paramount for optimizing drilling operations and preventing cuttings from settling at the wellbore’s bottom. Traditional methods rely on rotational viscometers, which are time-intensive, equipment-dependent, and lack real-time monitoring capabilities. This study underscores the feasibility of leveraging machine learning (ML) as a practical tool for predicting drilling-fluid gel strength, offering real-time monitoring and precise predictions to enhance drilling efficiency, safety, and automation initiatives. Background The gel strength of drilling fluid is assessed using a viscometer, focusing on the 3-rev/min reading obtained after agitating the fluid at 600 rev/min to disrupt any gel formation. Initially, the measurement is taken when the mud reaches a static state for 10 seconds. Subsequent readings are conducted at 10- and 30-minute intervals. The rationale behind the 30-minute reading lies in its ability to indicate whether the mud forms a substantial gel during prolonged static periods, such as when tripping out a bottomhole assembly. Elevated gel strength may result in increased pump pressure required to restore circulation after extended static conditions. Additionally, a consistent upward trend in the 30-minute gel strength suggests the accumulation of ultrafine solids. Consequently, appropriate measures such as chemical treatments or dilution with fresh base fluid are necessary to address this issue. The frequency of measuring various fluid properties is tailored to their respective effects on well-control and drilling operations. These frequent evaluations allow for timely adjustments and monitoring of rheological measurements, offering valuable insights into rock sensitivity and the performance of mud activity and stability after exposure to drilled formations. On the other hand, a complete mud test (including all mud rheological properties) is performed twice a day because it consumes considerable time. It has been observed that mud rheological properties exhibit a significant correlation with two fundamental mud properties: mud weight and Marsh funnel (MF) viscosity. To the best of the authors’ knowledge, a dearth of research exists in the literature aimed at predicting the gel strength of drilling fluid using ML techniques. Consequently, this research endeavor introduces a novel ML model designed specifically for forecasting the gel strength of synthetic oil-based mud systems. Such predictive models are poised to enhance drilling performance by optimizing mud functions. Leveraging MF and mud-density measurements, the developed models aim to forecast the rheological properties of drilling fluid, thereby facilitating improved monitoring of mud functionality during drilling operations at the rig site.

Influential mechanism of operational parameters on internal resonance of drill strings by numerical simulations

Abstract Drill string vibration is highly conductive to drill string fatigue and component failure. In this study, a finite element model of a drill string with bottom hole assembly (BHA) is constructed to investigate the effect of different operational parameters, such as different string length, density, pressure, and velocity of drilling fluid on drill string natural frequencies, and thus internal resonance by considering fluid-structure interaction (FSI) in ANSYS. Numerical simulations demonstrate that the natural frequencies decrease as the length of the drill string increases, which is especially true for the axial mode. The condition of 1:1 internal resonance between the axial and torsional modes only occurs when the length of drill string is sufficiently high. Nevertheless, this resonance fades away in the presence of fluid. The increment of fluid density slightly increases the natural frequency in lateral mode, whereas decreases that in axial mode. On the other hand, this effect of density is negligible in the torsional mode. The natural frequencies for axial, torsional and lateral modes decrease as the fluid velocity increases, and the impact of fluid pressure on natural frequency is almost not observable. The numerical results for the case without drill fluid are in qualitative agreement with analytical solutions. when considing the effect of drill length on natural frequency.

Real-Time Lithology Prediction at the Bit Using Machine Learning

Real-time drilling analysis requires knowledge of lithology at the drill bit. However, logging-while-drilling (LWD) sensors in the bottom hole assembly (BHA) are usually positioned 2–50 m (7–164 ft) above the bit (called the sensor offset), leading to a delay in real-time drilling analysis. The current industry solution to overcome this delay involves stopping drilling to perform a bottoms-up circulation for cuttings evaluation—a process that is both time-consuming and costly. To address this issue, our study evaluates three methodologies for real-time lithology prediction at the bit using drilling and petrophysical parameters. The first method employs a petrophysical approach, which involves using bulk density and neutron porosity predicted at the bit. The second method combines unsupervised and supervised machine learning (ML) for prediction. The third method employs classification algorithms on manually labeled lithology data from mud log reports, a novel approach used in this work. Our results show varying degrees of success: the bulk density versus neutron porosity cross-plot method achieved an accuracy of 58% with blind-well test data; the ML approach improved accuracy to 66%; and the Random Forest (RF) classification with manual labeling significantly increased accuracy to 86%. This comparative analysis of three different methodologies for lithology prediction has not been previously explored in the literature. While clustering and classification methods have been regarded as the most effective, our study demonstrates that they do not always yield the best result. These findings demonstrate that ML models, particularly the manual labeling approach, substantially outperform the petrophysical method. This new algorithm, designed for real-time applications, uses selected input parameters to effectively minimize problems associated with the sensor offset of LWD tools. It rapidly adapts to changes, offering a quicker and more cost-effective interpretation of lithology. This eliminates the need for time-consuming bottoms-up circulation to evaluate cuttings. Ultimately, this approach enhances drilling efficiency and significantly improves the accuracy of lithology prediction, notably in identifying interbedded geological layers.

How to mathematically model a drill-string: lumped or continuous models?

This work compares the efficacy of lumped and continuous models in simulating drill-string dynamics. We aim to critically explore the inadequacy of lumped models and challenge their perpetuated use in the literature. Lumped models represent the drill-string with a pre-determined number of discrete masses, sometimes as few as one or two. This inherently restricts their ability to capture the distributed nature of drill-strings, compromising their accuracy. In this paper, these limitations are made evident by comparing simulations of lumped models with simulations of continuous models that increase in complexity. First, predictions of the axial behaviour obtained with two models, one lumped and another continuous, are analysed. Second, simulations involving a 3-D fully coupled continuous model are evaluated. The simulations demonstrate the inaccuracy of lumped models. Also, they refute the frequent assumption of representing the bottom hole assembly (BHA) as a single lumped mass. Beyond these results, theoretical arguments based on fundamental wave-reflection phenomena are employed to further support the inadequacy of lumped formulations for this purpose. Third, this paper also discusses the prevalent strategy of validating lumped models through comparisons with laboratory experiments. This approach suffers from being a makeshift validation, as similitude principles are often violated in laboratory setups, resulting in a practice that may have helped perpetuate lumped models in the literature. Consequently, using lumped models for general drill-string dynamics prediction is not appropriate. Recognising their limitations and exploring alternative approaches, such as continuous models, is crucial for accurate drill-string dynamics prediction.

An Integrated Solution in Utilizing Active Magnetic Ranging to Seal Off Underground Gas Storage: Theoretical Analysis and Field Test

Summary In this paper, we describe a comprehensive technology based on an active magnetic ranging system (AMR) for sealing off the cement plug (CP) in the open hole (OH) section of the wellbore below the existing CP for underground gas storage. Utilizing depleted oil and gas reservoirs for natural gas storage is an important approach toward achieving carbon neutrality. Sealing off old wellbores is prioritized according to relevant standards. The challenge with OHs with CP is that there are no magnetic beacons in the wellbore, and the extent of compaction is unknown. Accurate placement of the seal-off CP is crucial because current technical methods, such as electromagnetic and acoustic waves, have limitations. Magnetic ranging technology, which is mature and widely used for wellbore interceptions or collision avoidance, requires magnetic beacons such as steel casing, drillpipes, or bottomhole assemblies left in the borehole. On the other hand, acoustic positioning techniques are applicable but presently complex to run operationally. In this paper, we propose a comprehensive control technology. It starts by measuring the positional relationship between the subject wellbore (SW) and a magnetic beacon wellbore (MBW) using AMR. The data are then used in combination with additional skew data along with associate positional uncertainty or ellipse of uncertainty (EOU) to determine the location of the target wellbore (TW) and the MBW. By calculating the relative positional relationship between the SW and the TW, OH reentry below CP can be achieved within the EOU below the sidetracking point. After reentry, specific work such as crushing, element logging, caliper logging, and full hydrocarbon gas detection is performed to verify if the TW is still in the original position and if the caprock is properly squeezed and sealed off. The comprehensive technique or method was tested on five wells in the Bohai Bay, successfully assessing the position of the OH wellbore and reentering below the CP. The process system expands the field of AMR and demonstrates significant industrial application value. It provides a new means of sealing off complex old wells.

التصميم ألامثل للعملية الهيدروليكية لرأس الحفر

All drilling companies emphasize the importance of maintaining optimum drilling bit hydraulics in real-time drilling operations. The behavior of flow rate and pressure plays a crucial role in monitoring and optimizing drilling processes. By ensuring the hydraulic conditions are optimal, various drilling-related issues such as equipment failure, wellbore instability, and kicks can be minimized, resulting in significant time and cost savings. The paper's main objective is to illustrate the impact of mud pump flow rate optimization on the cutting Transport Fluid Velocity (TFV). This optimization directly influences the pressure loss inside the drill string and annular space, which, in turn, affects the selection of optimum nozzle sizes. The goal is to achieve efficient bottom hole cleaning and hole conditioning, ultimately leading to satisfactory rates of penetration (ROP). The study conducted a series of tests using different pump flow rates ranging from 100 to 500 gallons per minute (gpm) to drill two different sections. An 8 ½" bottom hole assembly (BHA) with a Tri-cone bit and a 6 1/8" BHA with a Polycrystalline Diamond bit were used. The WellPlane Software was employed for optimization. The results of the study indicate that for the 8 ½" section, a minimum pump rate of 488.3 gpm is necessary to avoid cutting accumulation and the formation of bed height. On the other hand, for the 6 1/8" section, a minimum pump rate of 193.2 gpm is required. The optimal parameters for achieving a bed height of zero in the 8 ½" section are a pump flow rate of 500 gpm and nozzle size of (316). For the 6 1/8" section, a pump flow rate of 250 gpm and nozzle size of (514) are recommended. In summary, the optimization of bit hydraulics is essential for mitigating drilling problems and reducing overall drilling costs. By maintaining proper flow rate and pressure conditions, along with appropriate nozzle sizes, efficient bottom hole cleaning can be achieved, leading to improved rates of penetration and overall drilling performance.

Assisting Directional Drilling by Calculating a Safe Operating Envelope

Summary Nowadays, complex 3D trajectories are executed with a succession of circular arcs (CAs). Although they have constant curvature, their tool face is not constant. Consequently, directional drillers must adjust the tool face regularly to reach the target entry within its tolerances. This paper investigates the use of the constant curvature and constant tool face (CTC in short) curve as an alternative to the CA to assist the directional drilling work to reach the target entry within its boundaries. The problem is addressed by calculating a safe operating envelope (SOE) to reach the boundaries of the target entry and provide a tolerance window for the curvature and tool face to support directional drilling decisions. The target entry tolerance is discretized as a polygon. From the current bit position and its direction, the possible choices of curvatures and tool faces are obtained to reach the edges of the target entry shape. The SOE can be calculated with the CA or with the CTC curve. It is, therefore, possible to compare the advantages and disadvantages of both types of curves to attain the target entry and stay within its boundaries. The CA is shorter than the CTC curve. However, it requires adjusting the tool face during the navigation, which is not the case with the CTC curve. As a result, the directional driller can control the bottomhole assembly (BHA) direction such that the well lands within the target entry limits by using set points for tool face and curvature inside the calculated SOE. Furthermore, a new way to represent the SOE is introduced. It makes use of a 3D cylindrical representation where the curvature is mapped as the height of a cylinder, while the tool face corresponds to the azimuth in the cylindrical coordinate system, and the length is linked to the radial distance. This provides a visual aid to understand the SOE. Moreover, this visualization helps to appreciate the relationship between the initial bit location and direction in the construction of the SOE and how the margins increase in a particular manner as the bit approaches the target entry polygon. The CTC curve is the natural one followed by directional positive displacement motors (PDMs) or rotary steerable systems (RSS). Potentially, the CTC curve may be a more straightforward solution to automated directional drilling control because it is easier to be followed by both PDM and RSS.

Integrated Technique Provides Effective Water Diagnostics in Tight Sand

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper URTeC 3864145, “Evaluating the Hydraulic Fracture Through Acoustic Reflection Imaging and Production Logging for Water Diagnostic Beyond the Wellbore: A Case Study From Chang 8 Tight Sand in the Ordos Basin, China,” by Guangsheng Liu, Dajian Li, and Gang Zheng, PetroChina, et al. The paper has not been peer reviewed. _ The Triassic Chang 8 tight sand reservoir in the Xifeng block of the Ordos Basin features low permeability, which means that hydraulic fracturing and subsequent waterflooding were performed during its development phase. Water breakthrough was encountered after a short period of oil production. A solution of borehole acoustic reflection imaging combined with production logging was proposed in a horizontal well suffering from high water cut. The objective was to determine which stages contributed most to water production, understand the cause, and, ultimately, create a water shutoff plan. Introduction The Ordos Basin, with an area of approximately 2.5×105 km2, is in North China. The Upper Triassic Yanchang formation is subdivided into the Chang 1 to 10 members, from top to bottom. It contains significant oil reserves in siltstone and sandstone reservoirs, especially in Chang 6 through Chang 8, that have been the major oil-producing resources in recent years. In the Triassic Chang 8 tight sand reservoir, horizontal well drilling and multiple-stage hydraulic fracturing have become common practice. In the study block, the well of interest was hydraulically fractured by coiled tubing with sand-jet perforation and fracturing operations in one run with a retrievable packer in the bottomhole assembly of the coiled tubing. In the study block, when some producing wells encountered water breakthrough, traditional water diagnostics using production logging was not enough; a survey to detect hydraulic fractures beyond the wellbore was needed. Theory and Methods Borehole Acoustic Reflection Imaging. The processing workflow for acoustic reflected waves mainly consists of two parts. The first is a filtering process to suppress the borehole mode and noise in order to preserve the reflected wave. The second is to migrate the reflected wave to the true position of a reflector. The conventional migration method used for acoustic reflection imaging normally requests previous information relating to reflector dip and produces 2D images, which show the reflector shape but have hard-to-extract precise quantitative information. A trial reflector-migration method covered in the literature was introduced in 2016 that does not require input of structure dip and is of high resolution. A 3D slowness-time-coherence method was developed in 2018, also covered in the literature, that could determine the true dip, azimuth, and distance of a reflector.

Redundant Configuration Method of MEMS Sensors for Bottom Hole Assembly Attitude Measurement.

Micro-electro-mechanical systems inertial measurement units (MEMS-IMUs) are increasingly being employed for measuring the attitude of bottom hole assemblies (BHAs). However, the reliability and measurement precision of a single MEMS-IMU may not meet drilling's stringent needs. Redundant MEMS-IMU systems can effectively enhance the reliability and precision. This paper proposes a redundant configuration method for MEMS sensors tailored to BHA attitude measurement. Firstly, based on reliability theory and a cost-benefit analysis, considering factors such as cost, size, and reliability, the optimal number of sensors in the redundant system was determined to be six. Considering the structural characteristics of the BHA, a hollow hexagonal prism-shaped redundant configuration scheme was proposed, ensuring the circulation of drilling fluid within the drill pipe. Next, by employing Kalman filtering to integrate the output data from the six sensors, a virtual IMU (VIMU) was formed. Finally, experimental verification was carried out. The results confirmed that, after redundancy implementation, the velocity random walk of the accelerometer decreased by an average of 58% compared to a single MEMS-IMU, and bias instability was reduced by an average of 54%. The angular random walk of the gyroscope decreased by an average of 58%, and bias instability was reduced by an average of 37%. This research provides a theoretical foundation for enhancing the precision and reliability of BHA attitude measurements.

A physics-informed Bayesian data assimilation approach for real-time drilling tool lateral motion prediction

In this study, a Bayesian data assimilation method that fuses physics with motion sensor data is demonstrated to infer the dynamic states at points of interest on the bottomhole assembly (BHA) with proper uncertainty quantification. A 4.75 inch-LWD (Logging-while-drilling) tool has been used as a use case, where the dynamic states at the formation evaluation sensor can be predicted in real time with the measurements at the motion sensor as the required inputs. This was achieved with a developed transfer function that utilizes unscented Kalman filtering technique. The robustness of the transfer function was evaluated with synthetic data obtained from finite element analysis (FEA) simulations for various BHA configurations and drilling conditions. It was found that the prediction by the transfer function agrees favorably well with the true states of motion at the formation evaluation sensor. Specifically, using the developed transfer function can help reduce the relative errors for the motion trajectories at the formation evaluation sensor by a factor of 3, and can significantly enhance measurement quality risk classification. The developed transfer function method was further assessed with experimental roll test data, which is considered as close to drilling conditions. The prediction by the transfer function was found consistently close to the ground truth in the presence of backward whirl. The developed modeling method can potentially have broader impacts by enabling fit-for-basin virtual V&V (Verification and Validation) to accelerate LWD tool development, or enabling future drilling optimization.

An Analysis of Drilling Projection Uncertainty and Implications for Collision Avoidance Management Systems

Summary During well planning, specifying the separation that must be maintained from offset wellbores is critical to ensuring safe operations. Recent efforts on API RP 78, an upcoming American Petroleum Institute recommended practice for wellbore placement, have provided guidelines for calculating safe separation distances and engineering considerations for those calculations. A major milestone was the publication of a separation rule (Sawaryn et al. 2019) standardizing a formula for separation factor (SF), which in turn defines the minimum allowable separation distance (MASD) between two wellbores and the allowable deviation from plan (ADP) for a wellbore being drilled. One element of this formula, σpa, describes the accuracy with which a future wellpath can be predicted. Prior guidance provides a suggested value for σpa (1.6 ft or 0.5 m at 1-sigma) based on heuristics. A more rigorous approach for estimating this value is presented, where the design of the drilling program can be considered. A framework is proposed for modeling deviation from a projected path using a planned trajectory, bottomhole assembly (BHA) properties, and survey practices. The method identifies where a deviation is detected through survey measurements and estimates a planned recovery operation. Equations are provided for estimating the distance from plan at deviation detection along with the maximum expected deviation during recovery. Common drilling scenarios are analyzed for sensitivity to operational parameters such as survey course length, sensor offset, tool face control, and BHA performance. The impact of varying σpa is explored across prototypical collision avoidance cases. A discussion of the relationships between the σpa value and the common collision avoidance calculations, such as SF, MASD, and ADP, is included along with considerations for the design of a risk management policy. Survey course length, survey sensor offset, and uncertainty in directional performance are all shown to have a significant impact on the potential maximum deviation from plan. An additional factor considered is the aggressiveness expected when performing recovery operations. An analysis of common drilling scenarios suggests the previously provided guidance of 1.6 ft at 1-sigma appears suitable for cases where the directional behavior of the BHA is well characterized and the combination of course length and survey sensor offset is kept to 150 ft or less. Longer survey course lengths, larger sensor offsets, or uncertainty in directional performance of the BHA can produce larger σpa values, in some scenarios causing a significant impact on the MASD and ADP. Previous work has called attention to the uncertainty in drilling to a projection, but up to now, there has not been a rigorous method for estimating that quantity. With the methods outlined in this paper, well planners and drilling engineers can make more informed decisions on how to ensure safe separation practices in their own operations.

A data-driven bit projection system with motor yield prediction and advisory for directional drilling and well trajectory control

In the evolving of the oil and gas industry, where innovation and technological advancement are paramount, directional drilling stands as a pioneering technique that has revolutionized the extraction of hydrocarbon resources from beneath the Earth's surface. For drilling with mud motor, accurate projection of bit position from the latest survey and comprehensive evaluation of the current motor yield (MY) are essential to avoiding early well trajectory deviation and optimizing future directional plans. Currently, these responsibilities primarily rest on the shoulders of directional drillers (DDs), consuming valuable drilling operation time and being subject to biased human judgments. In this study, a data-driven bit projection system for directional drilling optimization and well trajectory control is developed. A kinematic model is first constructed for the projection of bit inclination (INC), azimuth (AZI), and north-east-vertical (NEV) in drilling with mud motors. Moreover, in scenarios involving curve section slide drilling, a machine learning model is developed to predict instant MYs observed between surveys, which is trained and tested on a dataset comprising drilling over 350 Delaware Basin curve section stands. Ultimately, a low MY reasoning algorithm is proposed to identify the dominant factor that causes the suboptimal MY output and provides recommendations for upcoming drilling plans. The proposed system is validated using 1189 vertical stands, 240 curve stands, and 1837 lateral stands from 17 different wells. The validation results illustrate that the bit NEV projection error averages below 0.82 ft for 90-foot surveys in vertical/lateral sections. In curve sections, the average MY prediction error is 0.96° one hundred feet or 7.6% in the relative sense and the average 30-foot bit NEV projection error is 0.228 ft, with the predicted MY as input. Compared with the physics-based bottomhole assembly (BHA) bending model and other data-driven approaches in the literature, the proposed system sees a large improvement in MY prediction and the bit NEV projection accuracies. With the minimal input data requirements, fast computation speed, and accurate projection/prediction results, the proposed bit projection system holds the opportunity of application in the autonomous directional drilling system, real-time drilling job evaluations, and well trajectory optimization.

IMU/Magnetometer-Based Azimuth Estimation with Norm Constraint Filtering.

A typical magnetometer-based measurement-while-drilling (MWD) system determines the azimuth of the bottom hole assembly during the drilling process by employing triaxial accelerometers and magnetometers. The geomagnetic azimuth solution is susceptible to magnetic interference, especially strong magnetic interference and so a rotary norm constraint filtering (RNCF) method for azimuth estimation, designed to support a gyroscope-aided magnetometer-based MWD system, is proposed. First, a new magnetic dynamical system, one whose output is observed by the magnetometers triad, is designed based on the Coriolis equation of the desired geomagnetic vector. Second, given that the norm of the non-interfered geomagnetic vector can be approximated as a constant during a short-term drilling process, a norm constraint procedure is introduced to the Kalman filter. This is achieved by the normalization of the geomagnetic part of the state vector of the dynamical system and is undertaken in order to obtain a precise geomagnetic component. Simulation and actual drilling experiments show that the proposed RNCF method can effectively improve the azimuth measurement precision with 98.5% over the typical geomagnetic solution and 37.1% over the KF in a RMSE sense when being strong magnetic interference environment.

Real-time prediction of bottom-hole circulating temperature in geothermal wells using machine learning models

Drilling high-temperature geothermal wells presents technical and economic challenges. Real-time and precise estimation of bottom-hole circulating temperature (BHCT) during geothermal drilling is crucial for maximizing the working life of drill bits and temperature-limited bottom-hole assembly (BHA) components, thereby avoiding unplanned and unnecessary bit/BHA trips. This study introduces a novel machine learning (ML) model that accurately predicts BHCT in real time, enhancing proactive temperature management and mitigating thermally induced challenges during geothermal drilling operations.An integrated thermo-hydraulic model, validated using publicly available data from the Utah FORGE field, was used to generate a large dataset that simulates the transient BHCT under typical drilling conditions. This dataset was subsequently used to train and test the prediction capability of six ML models of the BHCT, including deep neural networks (DNN), support vector machines (SVR), random forests (RF), extreme gradient boosting regressor (XGBoost), ensemble (Stacked) algorithm, and long-short term memory (LSTM) networks. It was also used to generate an understanding of the non-linear relationship between the input features and the output variable (BHCT). Resultsdemonstrate the benefits of implementing the LSTM model for reliable prediction of the BHCT and capturing its full-scale transient behavior in geothermal wells. The LSTM model stands out for its excellent generalization capability, stability, and precision in real-time estimation of BHCT across various geothermal drilling conditions, including both stationary and dynamic scenarios. This is achieved without the high computational costs associated with complex numerical models, thus preventing temperature-related drilling problems. Among the other supervised ML models, the XGBoost model can still reliably simulate the BHCT with a mean absolute error (MAE) below 1 °C during geothermal drilling at constant drilling parameters, but will show overfitting when drilling parameters change.

Estimation of Surge and Swab Pressures While Tripping for Minimizing Excessive Drilling Problems

Surge and swab pressures result from pipe movement upward/downward during drill string reciprocation and tripping. surge and swab create costly drilling concerns such well kick, formation breakage, and lost circulation. This study aims to find the optimum pipe tripping speed to avoid surge and swab issues, particularly in lost circulation zones. Also, to determine how drilling factors and well bore geometry affect surge and swab pressures. Mud rheology, mud properties, hole diameters, drill pipe diameter, and bottom hole assembly (BHA) dimensions were also analyzed. Dynamic surge and swab model was employed to simulate two case studies in Rumaila Iraqi oilfield. The findings indicated that the tripping speed is the most effective variable on surge and swab pressures. Annular clearance and BHA design have also a major effect on the surge and swab pressures. For the first case study, it is found that whenever the mud weight is far from the pore pressure and fracture pressure gradients, the 5" drill pipe can be tripped in/out of lost circulation formation (Shuaibba formation) at optimum tripping speed of (80 ft/min) without surge/ swab related problems. The reason is that the generated surge pressures (6110-6300 psi) are below the fracture pressure (7100-7400 psi). The results also showed that tripping 5" drill pipe within a maximum running speed of 80 ft/min in (8.5") open hole section through Tanuma formation till Rumaila formation causes a surge pressures of (4650-5050 psi) which is still below the fracture pressures of formations (4750-5660 psi). the results of the second case study (S-shaped well) revealed that the optimum tripping speed of the drill string in the (12.25") open hole through Dammam and Hartha formations is (90 ft/min). it is also concluded that pulling out of hole (POOH) process must be carried out more carefully than the running process since the mud density is near the pore pressure gradient. The results of this study can be further used to improve the drilling efficiency in Rumaila oil field with decreasing non-productive time (NPT) by employing the appropriate tripping speed and optimal drilling operations.

Failure Analysis of Large-Size Drilling Tools in the Oil and Gas Industry

Abstract The safety problem of large-size drilling tools in large-size boreholes has become increasingly prominent with the exploration and development of deep and ultradeep wells. This study analyzes the causes of large-size drilling tool failures from the engineering point of view via statistical analysis, experimental material test, and vibration and bending analyses. Results show that the violent downhole vibration changes the drilling tool's mechanical properties. These changes result in an uneven distribution of hardness and reduced impact work, finally leading to the initiation of fatigue cracks at stress concentration points. Drilling tool bending is closely related to drilling parameters and bottom hole assembly (BHA) configuration. Unreasonable BHA configuration and drilling parameters increase BHA bending and accelerate fatigue failure. Once a crack is generated, the corrosive ions in water-based drilling fluids invade the microcrack, causing the corrosion of the drilling tool material. As a result, the strength is reduced, and the fracture is aggravated. Therefore, measures for preventing the failure of large-size drilling tools are proposed. We hope that the results of this work can provide useful guidance for drilling engineers.

Steering ability rapid evaluation of the slide drilling system based on multi-body dynamics model

Efficiently and accurately predicting the steering ability of the bottom hole assembly (BHA) in slide drilling is a crucial yet challenging task. While the industry standard three-point geometry method is computationally efficient, it cannot capture the intricate mechanics involved in the drilling process. Conversely, utilizing the whole drill string dynamics model for simulating slide drilling provides a more comprehensive representation but involves time-consuming evaluations, making it difficult to balance precision and efficiency. This study addresses this challenge by proposing a rapid evaluation method that ensures both speed and accuracy by developing a multi-body dynamics rapid model of the slide drilling system. Based on the whole drill string model, this method incorporates two key techniques to achieve its primary objective. Firstly, it utilizes the equivalent torque model of the bit, which includes the fixed joint and the virtual rotational velocity, to replace the original revolute joint between the positive displacement motor (PDM) and the bit. Secondly, a segmentation model is established to decouple the simulation of the BHA drilling process from the drill string equilibrium process, thereby significantly reducing the slide drilling system’s degree of freedom (DOF). The proposed method offers a new approach to improving the efficiency of evaluating the steering ability of the slide drilling system while ensuring a high level of accuracy.

Investigation on fatigue life of push-the-bit rotary steerable bottom hole assembly with random bit-rock interaction

Rotary steerable systems are critical for challenging boreholes in deep-sea oil and gas drilling, where fatigue failure is the normal form of damage. A procedure with deterministic excitation and random excitation is presented in this paper to reliably predict the fatigue life of the bottom hole assembly. The initial defects, the Coulomb friction model, frictional contact between the drill bit and rock, and the stochastic rock-cutting process are included in the model. Monte Carlo approach is used to obtain the Statistical characteristics of the stochastic model. Based on the program mentioned above, influences of some parameters, such as rotational speed, weight on bit, steering force, and random excitation on torsional vibration characteristics, are investigated. Moreover, the rain-flow counting method is applied to reveal the dependency relationship between fatigue life and torsional vibration. It is found that random excitation can exacerbate the torsional vibration phenomenon and even significantly reduce the fatigue life. Finally, compared with the deterministic system, the sensitivity index coefficient of the fatigue life in the random excitation model is about 0.8 % - 2.2 % higher. The research results can provide a theoretical basis for reducing tool failure in on-site deep-sea oil and gas drilling.

Plug Your Way Through Downhole Restrictions

_ Unable to successfully deploy plug-and-perf bottomhole assemblies (BHA) to the desired depth has resulted in significant nonproductive time (NPT) in unconventional completions. These instances of NPT are primarily attributed to casing deformation, rather than plug presets. To address these downhole restrictions, frac plugs with smaller outer diameters (OD) were introduced for stage isolation. This reduction in plug OD minimizes the risk of getting stuck in tight spaces, but it also compromises pressure ratings. This raises the risk of skidding (slip losses, anchoring) and leads to increased fluid usage for pumpdown. These challenges not only risk well productivity, but also escalate completion time and costs. For a comprehensive solution, a smaller-OD frac plug is necessary to pass through tight spots, while maintaining anchoring, sealing, and reducing required pumped-fluid volume. The Gap The annular clearance between the plug OD and casing inner diameter (ID) significantly influences plug-and-perf operations. A smaller gap leads to advantages such as lower expansion rates for isolation, better anchoring, and reduced pumped-fluid volume, but it also heightens the risk of obstructions. Conversely, a larger gap requires higher expansion rates for isolation, resulting in weaker anchoring, lower pressure rating, and increased fluid consumption, but reduces the likelihood of obstructions. In some frac operations, higher pressure is needed to break down the formation; thus, frac plugs with higher pressure ratings (smaller gap) are commonly favored. For instance, in 5.5-in., 20-lb/ft casing, typical frac plugs have an average OD of 4.4 in., an expansion rate of 8–12%, and a pressure rating of 10,000 psi. In many 5.5-in., 20 lb/ft casedhole completions across the US and parts of China, the annular clearance between casing ID and frac plug OD is approximately 0.2 in. on the x-axis and 0.4 in. on the y-axis (Fig. 1). In this confined space, encountering debris, sand accumulation, or a deformed section during pumpdown can obstruct or fully trap the plug. To mitigate these uncertainties, smaller-OD plugs are used for such “emergency” scenarios. Smaller-OD plugs have improved chances of navigating through tight spots, but they necessitate higher expansion rates for isolation, resulting in lower pressure ratings. For example, in 5.5-in., 20 lb/ft casing, reduced OD plugs have an average OD of 3.8 in., an expansion rate of 20–25%, and a pressure rating of 5,000 psi. They are more likely to fail due to their pressure limitations and use more fluid for pumpdown. In cases where the use of normal-OD plugs is not feasible, opting for smaller-OD plugs, even though they might have a higher risk of failure, can be a valuable last resort. This approach is sometimes favored over entirely skipping the problematic stages without any form of stimulation.

Investigation and Analysis of Influential Parameters in Bottomhole Stick–Slip Calculation during Vertical Drilling Operations

The critical factors that affect bottomhole stick–slip vibrations during vertical drilling operations are thoroughly investigated and analyzed in this research. Influential factors, such as rotation speed, weight on bit (WOB), bottom hole assembly (BHA) configuration, and formation properties, were studied in order to understand their part in the stick–slip phenomena. The analysis is based on a thorough review of previous research conducted on stick–slip drilling vibrations. A mathematical model was created that not only explains axial vibrations but also includes the torsional vibrations present in stick–slip occurrences, which helps with understanding the stick–slip phenomena better. This model can be used as an analytical tool to predict and evaluate the behavior of drilling systems under various operational circumstances. Furthermore, two drilling tests using a WellScan simulator were performed to validate the research findings and assess mitigation techniques’ viability. These test scenarios reflect the stick–slip vibration-producing situations, allowing us to test mitigation strategies. The finding of this study shows the effectiveness of two tactics for reducing stick–slip vibrations. First was the reduction of WOB, which successfully lowered the occurrence of stick–slip vibrations. The second was the increase in the rotation speed, which helped to control the stick–slip problem and increased the drilling speed. This study explains the complex dynamics of stick–slip vibrations during vertical drilling and offers practical, tried-and-true methods for reducing their adverse effects on drilling operations.