Mud Flow Rate Research Articles

Open-hole extension limit of offshore extended-reach well considering formation collapse

The current extension limit prediction model for offshore extended-reach well (ERW) in mudstone does not consider the formation collapse, which poses a huge risk to offshore drilling construction. To address this problem, this paper presents new open-hole extension limit prediction model for ERW. By considering formation collapse, rate of penetration (ROP), and annular pressure loss, the extension limit models during normal drilling and tripping were derived. The sensitivity of geological and engineering factors was evaluated by analyzing limits for wells 1H and 2H. The research results showed that: (1) The extension limit increases with the ROP and formation collapse duration, but decreases with the increase in mud weight, plastic viscosity, and flow rate. (2) In ERWs, the mud flow rate has a significant impact on the extension limit than the plastic viscosity of mud fluid. However, mud weight has the least impact compared to the two. (3) Considering various parameters, the predicted extension limit of well 1H, when the mud weight is 1.16 g/cm3 [9.67 ppg], is 1593.28 m [5225.96 ft] less than the limit when the collapse period is not considered.

Volume Calculation of Sidoarjo Mud Using TLS Data and Numerical Methods

Sidoarjo Mud is one of the phenomena of mud volcanoes located in the northern part of Java Island. A mud volcano is a phenomenon where mud material is released from the earth due to pressure (eruption). The mud continuously flows and accumulates around the central embankments. This phenomenon has caused the embankments to break several times due to the uncontainable mud volume. Observing the volume of Sidoarjo Mud is expected to help mitigate this problem. The Sidoarjo Mud volume was calculated using point cloud data obtained from Terrestrial Laser Scanner (TLS). Numerical methods such as the Trapezoidal and Simpson rules were employed to determine the mud volume. These numerical methods involve approximating the volume of irregularly shaped earthwork surfaces using mathematical techniques. The numerical method approximates the area under a trapezoid or curve representing the cross-section of the earthwork. In this study, kriging interpolation was conducted with a grid size of five meters. The relative difference between the numerical methods was found to be within acceptable limits, not exceeding 2.78% based on the American Society for Testing and Materials (ASTM) 2002 and not exceeding 2% based on ASTM 1998 as an industry acceptance error. Considering the relative difference results and the institutional report, the Trapezoidal method with a 5-meter grid size was considered the accurate volume calculation method. Based on the processed data, the total volume of Sidoarjo Mud within the embankment was 32,793,917.171 m3 in February 2022, 32,889,012.793 m3 in April 2022, and 33,390,051.407 m3 in June 2022. The volume calculation results show a difference of 95,095.622 m3 between February-April and a difference of 501,038.613 m3 between April-June. The mud flow rate for the February-April period was calculated as 1,872.114 m3/day, while for the April-June period was determined as 9,278.492 m3/day.

Analysis of a drilling mud-based system on the common problems related to coiled tubing application in slim-hole oil wells

Coil tubing is slim and looks like a long, continuous length of pipe made from carbon steel metal that is a lesion on spool that is 1 to 3.25 inches in diameter of 26,000 feet long. The main benefit of coil tubing in drilling operations over wireline jobs is the ability to pump chemicals through the coil and the ability to push it into the hole rather than relying on gravity. Inappropriate selection of the drilling mud is one of the contributing factors to hole problems. Different experiments were conducted to determine the mud rheology of multiple mud samples. Certain parameters, like the critical velocity, are calculated using a numerical approach for the coiled tubing applications. In addition, it is crucial to determine the pump pressure required to maintain a specific flow rate. It is noted that drilling operations become more efficient at lower plastic viscosities; however, plastic viscosity is reduced through dilution; hence, the rate of penetration is improved. Moreover, a higher yield point is capable of transporting the cuttings more effectively than a lower yield point. The critical velocity indicated the boundaries between the laminar and turbulent flow regimes. As the mud flow rate inside the tubing increased, the velocity increased, causing the shear stress at the tubing wall to increase.

Influence of drilling mud pulsations on well cleanout efficiency

Purpose. Determination of the influence of the non-stationary flow regime of the drilling mud on the efficiency of cleaning the wellbore in the annulus from drill cuttings. Methodology. The study on the carrying capacity of the drilling mud in a laboratory installation is carried out by simulating the process of its pulsations at different frequencies. The choice of the studied frequencies was made on the basis of previous studies. The evaluation of the influence of factors on the efficiency of rock removal was carried out using Latin experimental plans, which allowed us to evaluate the influence of the selected factors with a minimum number of experiments without losing the quality of the result. Findings. The influence of factors (mud flow rates, eccentric placement of the drill string, plastic viscosity of the drilling mud, pulsation frequency, rotation of the drill string) on the efficiency of cuttings removal along the annular space of the wellbore is analyzed. Three factors with the best interaction were found, which made it possible to build dependencies of their influence on the efficiency of rock removal on the surface. The effect of changing the frequency of pulsations of the drilling mud has been studied, and graphical dependences of their influence on the decrease in the volume of rock particles in the annular space have been obtained. Originality. Based on the results of experimental studies, the effectiveness of the impact of drilling mud pulsations on cleaning the well from rock particles has been proven. Practical value. The effectiveness of the use of drilling mud pulsations for hydrotransportation of cuttings along the horizontal section of the wellbore has been confirmed.

Prediction model of drilling wellbore temperature considering bit heat generation and variation of mud thermophysical parameters

Downhole tools are at risk of high-temperature failure during drilling operations in deep and ultra-deep wells. To solve this problem, researchers have developed temperature models for various drilling conditions to determine the wellbore temperature distribution. Unfortunately, few researchers have studied downhole tool temperatures compared to wellbore fluid temperatures. To the best of our knowledge, very few models have taken into account both the bit heat generated and the axial heat conductivity in the drill pipe to accurately predict downhole operating tool temperatures. In this study, a transient temperature model coupled with mud-drillpipe-casing-cement-formation is developed. Polycrystalline diamond compact (PDC) bit frictional heat generation equations and fitted curves of drilling fluid thermophysical parameters with temperature and density are considered in the model. Then, the effects of mud systems, density, flow rate, inlet temperature, rotary speed, and weight on bit (WOB) on the wellbore temperature and downhole tool temperature are discussed, based on the example of a well in Sichuan, China. The results of this study are an important guide for downhole tool selection and drilling parameter design. The model developed in this study has been used to guide the field operation of several oil wells in Sichuan and Qinghai.

A new approach for real-time prediction of stick–slip vibrations enhancement using model agnostic and supervised machine learning: a case study of Norwegian continental shelf

Efficient and safe drilling operations require real-time identification and mitigation of downhole vibrations like stick-slip, which can significantly diminish performance, reliability, and efficiency. This pioneering research introduces a robust machine learning approach combining model-agnostic regression techniques with Bayesian Optimized Extra Trees (BO_ET) to accurately predict stick-slip events in real-time using downhole sensor data. The model is rigorously tested and validated on a substantial offshore dataset comprising over 78,000 data points from a Norwegian continental shelf (NCS) oil field. The key input features encompassing real-time downhole and surface drilling parameters are carefully selected, including critical variables such as collar rotational speed, shock risks, annular pressure, torque, mud flow rate, drill string vibration severity, and other relevant measurements. These parameters offer significant insights into the occurrence of harmful stick-slip vibrations. Among several sophisticated machine learning models, the Extra Trees (ET) algorithm demonstrates superior performance with the lowest errors of 5.5056 revolutions per minute (r/min) Mean Absolute Error (MAE) and 9.9672 r/min Root Mean Square Error (RMSE) on out-of-sample test data. Further hyperparameter tuning of the ET algorithm via Bayesian Optimization dramatically reduces errors down to 0.002156 MAE and 0.024495 RMSE, underscoring the significant innovation and advantages of the proposed approach. By seamlessly incorporating real-time downhole sensor data and drill string mechanics, the model enables reliable identification of stick-slip events as they occur downhole. This grants opportunities to optimize critical drilling parameters including revolutions per minute (RPM), weight-on-bit (WOB), mud flow rates, and more to effectively mitigate stick-slip severity and improve the rate of penetration (ROP). Integrating the approach into automatic driller systems on offshore rigs offers immense benefits for drilling operations through substantially increased efficiency, fewer premature failures, lower costs, and significantly improved productivity and safety. Overall, this research strongly emphasizes the immense transformative potential of advanced data analytics and machine learning in enabling more efficient, economical, and sustainable drilling practices. The proposed model demonstrates clear superiority over existing methods and establishes a robust and reliable platform for real-time stick-slip prediction and mitigation, maximizing drilling performance.Graphical abstract

Application of Computational Fluid Dynamics for Investigation the Effect of the Hole Cleaning Parameters in Inclined and Horizontal Wells

The increasing global demand has prompted the development of more innovative ways to enhance the drilling of oil wells at lower costs, and avoid operational problems that affect the speed of drilling oil wells. The numerical cuttings trajectories simulation has been done to include the effect of cuttings collisions using commercial ANSYS FLUENT 2019 R3 CFD software. The (Eulerian-Eulerian) model was used to verify the cuts transport behavior due to the existence of liquid and solid phases. In this simulation, the mind transport rate is checked by changing the operational parameters which including (drilling mud flow rate and temperature, cuttings size, inclination, drill pipe rotation and eccentricity). The results show that the high degree of agreement was observed between the numerical results with experimental studied by the researcher Yaacob, indicating the CFD analysis system's dependability and capacity to mimic the drilling operation. The use of (Eulerian-Eulerian) model is found reliable in interpreting the phenomena of multiphase flow for understanding the mechanism of influence of parameters associated with the process of drilling oil wells on the lifting capacity. Increasing the flow velocity of the drilling mud transforms the flow pattern from laminar to turbulent, and the latter is one of the desired flow patterns during the flow that enable to increase the lifting capacity of the cuttings. The effect of the rotation speed of the drill pipe on the concentration of cuttings decreases when the flow rate of drilling fluid increases. the cuttings concentration when the flow velocity is 0.6 m/s reaches 48 % when the cuttings size is (0.5-1) mm and it attained to (60,57.52) % when the cuttings size is ((3.5-4) ,(2.25-3),(1.5-2)) mm respectively for the same flow velocity. The increase in the temperature of the drilling fluid weakened the ability of the drilling fluid to move the cuttings. At the flow velocity is 1.2 m/s and the drilling angle is 0˚ (vertical well), the cuttings concentration attained to 30 % within the annular space, while the concentration becomes (41, 44, 54, 32) % at the drilling angle (30˚, 45˚, 60˚, 90˚) respectively at the same stated flow velocity.

Real-time prediction of formation pressure gradient while drilling

Accurate real-time pore pressure prediction is crucial especially in drilling operations technically and economically. Its prediction will save costs, time and even the right decisions can be taken before problems occur. The available correlations for pore pressure prediction depend on logging data, formation characteristics, and combination of logging and drilling parameters. The objective of this work is to apply artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) to introduce two models to estimate the formation pressure gradient in real-time through the available drilling data. The used parameters include rate of penetration (ROP), mud flow rate (Q), standpipe pressure (SPP), and rotary speed (RS). A data set obtained from some vertical wells was utilized to develop the predictive model. A different set of data was utilized for validating the proposed artificial intelligence (AI) models. Both models forecasted the output with a good correlation coefficient (R) for training and testing. Moreover, the average absolute percentage error (AAPE) did not exceed 2.1%. For validation stage, the developed models estimated the pressure gradient with a good accuracy. This study proves the reliability of the proposed models to estimate the pressure gradient while drilling using drilling data. Moreover, an ANN-based correlation is provided and can be directly used by introducing the optimized weights and biases, whenever the drilling parameters are available, instead of running the ANN model.

Evolution and modeling of mine water inflow and hazard characteristics in southern coalfields of China: A case of Meitanba mine

In this paper, the hydrogeological characteristics in the southern coalfields of China are first briefly outlined. Then, taking the Meitanba mine as an example, the evolution and modeling of mine water inflow are studied. Finally, the hazard characteristics related to mine water and mud inrush are analyzed. The results show that the main mine water sources in the Meitanba mine area are groundwater, surface water and precipitation. The evolution of mine water inflow with time indicates that the water inflow is closely related to the development of karst structures, the amount of water from rainfall infiltration, and the scope of groundwater depression cone. The mine water inflow increases with time due to the increase in mining depth and the expansion of groundwater depression cone. Using the big well method and following the potential superposition principle, a hydrogeological model considering multi-well interactions has been developed to predict the mine water inflow. Based on the monitored data in the Meitanba mine area over a period of nearly 60 years, it is found that with increasing mining depth, the number of water and mud inrush points tended to decrease. However, the average water and mud flow rate per point tended to increase.

Generation of Synthetic Sonic Slowness Logs From Real-Time Drilling Sensors Using Artificial Neural Network

Abstract The acoustic data in terms of compressional and shear wave velocity provide important petrophysical information about the rock. The sonic data are a significant input that is commonly used for deriving geomechanical parameters. Understanding the geomechanical properties of reservoir rock is essential during the drilling, development, production, and stimulation of an oil or gas reservoir. Among them, Young's modulus and Poisson's ratio are the most important elastic parameters. These properties are usually estimated from bulk density, compressional, and shear wave velocity log data. Sonic data acquisition is usually achieved through dipole sonic imager log or laboratory testing on core samples which is costly and time-consuming. Acquiring sonic data from wireline logs is not a feasible approach all the time, as the wireline log, specially shear-wave log, may not be recorded for every well. However, drilling data are available in real-time for every well using real-time drilling sensors. The main objective of this paper is to predict sonic slowness logs in real-time based on the drilling data using artificial neural network (ANN). The data used in this study were recorded during the drilling of 12¼″ hole sections from two wells. Many formations of different lithology were penetrated while drilling these sections of over 3000 ft vertical interval. The drilling and sonic data sets were recorded and preprocessed before using them for the ANN model. About 2900 data points from the first well were used for building and testing the model. The input parameters included weight on bit (WOB), torque (T), standpipe pressure (SPP), pipe speed (PS), rate of penetration (ROP), and mud flowrate (Q). Another data set of 2000 data points from the second well that was drilled in the same field was used to validate the model. The predictions were compared with sonic logs that were obtained after the drilling operation, and the results appear to be highly promising for future applications. The sonic slowness ANN models showed high accuracy for the model building (training and testing). Validation of these models was carried out using an unseen data set. The results using the validation data set for the compressional slowness model yielded a coefficient of determination (R2) of 0.983 and average absolute percentage error (AAPE) of less than 1.25%. For the shear slowness model, R2 was higher than 0.994 and AAPE less than 1.175%. The study offers empirical correlations that can be utilized to estimate the sonic slowness logs by engineers without the need to employ ANN software. The new shear slowness correlation was compared with other widely used correlations and the results showed high accuracy.

Lifting capacity efficiency using polyethylene beads: A numerical investigation


 
 
 
 Global demand growth has driven the development of more inventive methods for enhancing oil well drilling at lower prices and avoiding operational issues that slow down oil well drilling. The present research is significant because the lifting capacity may be increased by inserting polymer beads into drilling mud instead of high-cost additives. The numerical cuttings trajectory simulation was performed using the commercial ANSYS FLUENT 2019 R3 software to account for the influence of cuttings collisions. To test the cuts transport behavior owing to the presence of liquid and solid phases, the (Eulerian-Eulerian) model was utilized. The mind transfer rate is determined in this simulation by varying the operating parameters (drilling mud flow rate and temperature, cuttings size and inclination, drill pipe rotation and eccentricity) with and without polyethylene (PE) beads. The result show that the average error ratio between the results of the numerical simulation is 5 % with the experimental results of researcher Ismail. The higher the percentage of PE beads entering with the drilling fluid, the lower the concentration of the cuttings within the annular space of the simulation model. The concentration of cuttings within the annular space reaches 28 % when drilling fluid flows at a speed of 1.2 m/s without adding polyethylene PE beads. While it decreases to (17, 21, 24) % when adding beads by (6, 4, 2) %, respectively, at the same flow velocity of drilling fluid. The decrease in the concentration of cuttings within the annular space of the simulation model reaches 14 % when PE beads are inserting with drilling fluid by 6 % and the drill pipe rotation speed is 0 rpm, While the percentage increases to 65 % when the drill pipe rotation speed is increased to 120 rpm at the same ratio of PE beads entering with the drilling fluid. The reduction percentage of the cuttings concentration within the annular space of the simulation model reaches 30 % when 6 % of PE beads are entered into the drilling fluid at a temperature of 20 ℃, while the percentage is reduced to 14 % when the drilling fluid temperature is 50 ℃ at the same percentage of PE beads is inserting. The inserting of polyethylene (PE) beads with the drilling fluid has increased the ability of the drilling fluid to move the cuttings, but it is affected by the amount of drilling angle, as we found that the effect of the polyethylene (PE) beads is effective and clear when the drilling angle is 0˚ (vertical). While its effect becomes less at the drilling angle of directional wells and becomes very weak at the drilling angle of 90˚ (horizontal).The inserting of polyethylene (PE) beads with drilling fluid has a good and positive effect with large-sized cuttings when compared with the impact of the beads with smaller-sized cuttings.
 
 
 

Data-Driven Modeling Approach for Pore Pressure Gradient Prediction while Drilling from Drilling Parameters.

Real-time prediction of the formation pressure gradient is critical mainly for drilling operations. It can enhance the quality of decisions taken and the economics of drilling operations. The pressure while drilling tool can be used to provide pressure data while drilling, but the tool cost and its availability limit its usage in many wells. The available models in the literature for pressure gradient prediction are based on well logging or a combination of some drilling parameters and well logging. The well-logging data are not available for all wells in all sections in most wells. The objective of this paper is to use support vector machines, functional networks, and random forest (RF) to develop three models for real-time pore pressure gradient prediction using both mechanical and hydraulic drilling parameters. The used parameters are mud flow rate (Q), standpipe pressure, rate of penetration, and rotary speed (RS). A data set of 3239 field data points was used to develop the predictive models. A different data set unseen by the model was utilized for the validation of the proposed models. The three models predicted the pore pressure gradient with a correlation coefficient (R) of 0.99 and 0.97 for training and testing, respectively. The root-mean-squared error (RMSE) ranged from 0.008 to 0.021 psi/ft for training and testing, respectively, between the predicted and the actual pore pressure data. Moreover, the average absolute percentage error (AAPE) ranged from 0.97% to 3.07% for training and testing, respectively. The RF model outperformed the other models by an R of 0.99 and RMSE of 0.01. The developed models were validated using another data set. The models predicted the pore pressure gradient for the validation data set with high accuracy (R of 0.99, RMSE around 0.01, and AAPE around 1.8%). This work shows the reliability of the developed models to predict the pressure gradient from both mechanical and hydraulic drilling parameters while drilling.

Study on Vibration of Directional Drill String with Affecting the Important Parameters with Energy Considering

A vibrant model for drill string in inclined well drilling is presented. Also, the effects of weight on bit, drilling mud flow rate and vibration of the drill string are analyzed analytically. The vibrations of drill string may bind optimizing the power and advantages of drill string that is an important problem for optimization and design of it. Dynamic equation of the model is introduced with consider of the axial displacement and lateral bending geometric nonlinear coupling. The effect of drilling mud flow is modeled using Paidoussis formulations considering energy formulation. Equation of the motion for the rotating drill string is derived utilizing Lagrangian technique and implementing FEM to analyze and solve these equations. The obtained outcomes show the nonlinear effects are important on the obtained results and findings. The effects of the drilling mud flow rate and weight on bit on the natural frequencies and time responses are evaluated. Improvement and development of the drilling mud flow rate results in decreasing of natural frequencies and vibrational amplitude, while increasing the weight on bit, leads to reduce of the natural frequencies and enhance the vibration amplitude clearly.

Analysis of the Surface Subsidence of Porong and Surrounding Area, East Java, Indonesia based on Interferometric Satellite Aperture Radar (InSAR) Data.

Since 2006, the mud volcano erupted in the Porong area due to wellbore failure triggered by an earthquake (2006) epicenter in the Jogjakarta area. The mud volcano buried several villages with mud and continued erupted until today. Based on the InSAR data, it can be seen that the subsidence is still happening near the dam area and another area that is not related to mud volcano eruption such as the production of two gas fields in the Porong area. Moreover, the Porong area is flat and low, less than 4 meters above sea level. The analysis shows that the subsidence rate in this area is up to 0.5 m/yr. If this subsidence is continuing, the city can be sinking and flooding during the rainy season. The prediction result from this method is about 10 years more and 36 years since in 2006 based on the mudflow rate method.

Study of mud weight window of horizontal wells drilled into offshore natural gas hydrate sediments

Drilling horizontal wells into natural gas hydrate (NGH) sediments may be one of the most promising methods to increase the cost effectiveness of the exploration of NGH. However, many challenges, such as wellbore collapse and wellbore fracturing, will be encountered. Therefore, an accurate prediction of the mud weight window (MWW) is very important. In this work, a model was built to calculate the MWW of horizontal wells drilled into offshore NGH sediments, considering the NGH saturation and the effects of inlet parameters of the drilling mud, and was combined with the transient heat transfer model to calculate the temperature distribution of the borehole. A case study was carried out, and the effects of several parameters were discussed: 1) When drilling horizontal wells in NGH sediments, the dissociation of NGH in the formation will not occur. 2) With increasing circulation time, the borehole will be cooled, and the cooling effect will lead to a decrease in both the fracture pressure and collapse pressure of the target zone. 3) The mud flow rate has a large influence on the mud temperature profile, especially in the horizontal section, and a higher mud flow rate leads to a lower fracture pressure and collapse pressure in the target zone. 4) The inlet temperature has limited influences on the mud temperature profile in the horizontal section and the MWW of the target zone. 5) The saturation of NGH in a formation has a significant influence on the collapse pressure but little influence on the fracture pressure, and higher saturation will lead to a wider MWW. This study will support the safe control of well stability and application of horizontal wells drilled into offshore NGH sediments.

Coupling rate of penetration and mechanical specific energy to Improve the efficiency of drilling gas wells

Drilling operations for oil or gas wells are very expensive. Optimizing the drilling efficiency and increasing the rate of penetration (ROP) will reduce the overall cost of the drilling operation. Different approaches are utilized to increase the drilling performance including analytical and empirical methods. However, most of the available models have some limitations once they applied for real-time drilling operations. This study presents a new approach for evaluating and improving the drilling operations for real-time applications. Seven ROP models were developed using artificial neural network (ANN) technique. The ANN models were developed using real field data (20,000 data sets) which includes the real-time recording of the surface drilling parameters such as rate of penetration (ROP), weight on bit (WOB), torque, rotation speed (RPM) and mud flow rate (Q). The ANN-based models are able to provide an accurate estimation for the full ROP profile. Thereafter, the predicted ROP was coupled with the calculated MSE in order to optimize the drilling performance. Moreover, and for the first time, a new (ROP/MSE) ratio is suggested, which can be used to assess the drilling operations in a real-time. A new profile of ROP/MSE ratio can be displayed along with the drilling parameter in order to provide a quick and more reliable evaluation for the ongoing drilling operation. The suggested ratio incorporates the impacts of the primary drilling factors which are the drilling speed (ROP) and the required drilling energy (MSE). Also, the seven ANN-based models, developed in this work, can predict the full profile of ROP with an average absolute percentage error (AAPE) of around 7.9% and a correlation coefficient of around 0.92.

Effect of the nozzle structure of the large-diameter slurry shield cutterhead on the scouring characteristics

The mud cake of the large-diameter slurry shield severely affects the tunneling efficiency and construction safety, the avoidance and elimination of which largely depends on the scouring characteristics of the nozzle. Based on the solid–liquid two-phase flow theory and dynamic mesh technology, this paper establishes a mud flow model of the nozzle on a slurry shield cutterhead and a cutterhead rotation model and builds a simulation model of the cutterhead nozzle scouring process with CFD. By verifying the simulation model with the self-developed 1 Mpa pressure-bearing scouring test bench, the paper conducts an analysis on how the convergence angle, outlet diameter, and length–diameter ratio of the 12 m large-diameter slurry shield cutterhead affect the scouring characteristics of the nozzle. The results show that when the convergence angle is 13°, the flow fields will be more uniformly distributed inside the nozzle, the average flow rate will be maximized, reaching 3.29 m/s, and the pressure loss will be minimized, thus leading to a relatively good scouring performance. With the assurance of both high flow speed and low pressure loss, the nozzle outlet diameter can be set between 30 and 60 mm for optimal flushing effect; at this point, the average mud flow rate is no less than 3 m/s, and the pressure loss is no more than 106 pa, which can help solve the caking problem to some extent. With the increase in length–diameter ratio, the loss of static pressure and total pressure witnessed a relatively high rise, as result of which a smaller long-diameter ratio will be more appropriate, also considering the mud flow rate reaches a maximum value of 3.24 m/s when the ratio is 3 and satisfying results could be achieved when the above ratio has the value of about 3.

Анализ работы алмазных долот при строительстве скважин в сложных условиях

The purpose of the study has been to analyze the operation of diamond drill bits of a PDC type (polycrystalline diamond cutters) in the regions with a complex geological section, and to develop recommendations on optimizing the drill bits. The PDC drill bits are originally designed for soft to medium-hard rocks, thus being ineffective for complex geological sections. As part of the research, the mechanics of the build-up formation on the drill bit cutter and its impact on the rock destruction have been studied. The influence of the pumped drilling mud volume and the pressure differential in the downhole motor on the mechanical drilling speed of the PDC bit has been analyzed. Proposals on improving the geometry and orientation of the tool cutters and optimizing the design of the cutting structure calibratation site and the bit blades have been given; measures on reducing the bottomhole vibrations of the bit during its operation have been suggested. As a result of the study, the mechanism of the build-up formation on the cutter’s working edge and its advance influence on the fracturing in the rock volumetric stratum has been determined. It has been found that the maximum feed of the drilling mud results in the complete absence of the build-up formation and a sharp increase in the mechanical speed of drilling. The study has shown the high performance of high-torque downhole screw motors and defined the optimum range of the pressure differential for the PDC drill bits as a function of the drilling mud flow rate. The authors have suggested the ways to reduce the vibration and stabilize the PDC drill bits by optimizing the structure and geometry of the tool’s cutters and blades, and by using hybrid cutters as auxiliary ones. The conclusion is that the optimization of the PDC drill bits enhances their operation performance under complicated geological-engineering conditions in Eastern Siberia and Yakutia.

Intelligent Drilling Advisory System Optimizes Performance

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper IPTC 19269, “Optimization of Drilling Performance Based on an Intelligent Drilling Advisory System,” by Mahmoud Abughaban, SPE, and Amjad Alshaarawi, SPE, Saudi Aramco, and Cui Meng, Guodong Ji, and Weihong Guo, CNPC, prepared for the 2019 International Petroleum Technology Conference, Beijing, 26–28 March. The paper has not been peer reviewed. Copyright 2019 International Petroleum Technology Conference. Reproduced by permission. In the current work, a rig advisory system is developed to continually improve rate of penetration (ROP) and drilling performance. An intelligent drilling advisory system (IDAS), based on a soft closed-loop solution with multiple regression analysis—called optimum parameters global retrieval—has been established. As an effective tool for further achieving the optimal depth of cut (DOC), the control system led to satisfactory outcomes that overcame drilling challenges in Saudi Arabia and China, thereby serving as a step toward automated drilling operations. Introduction The IDAS was developed to inform drillers of optimal weight on bit (WOB), rotary speed, and mud-flow rate to penetrate rock and achieve higher ROP and longer bit runs. Optimized drilling parameters are calculated and updated using a soft closed-loop solution, which monitors the ROP and energy input to the bit in real time by means of a mud logger and topdrive system controller on the rig site, and calculates parameters by maintaining an optimal relationship between the ROP and energy input. If the ROP is under expectation, it automatically evaluates new conditions and updates optimal parameters by maintaining a proper relationship between the ROP and energy input. The following features of the IDAS improve drilling performance: A combination of evaluation factors [such as DOC and drilling specific energy (DSE)] that may be advantageous to drilling performance. Simple optimization for ROP improvement may not achieve maximum potential drilling performance given current drilling technologies and geology, and the consideration of ROP over all other factors generally leads to serious bit wear. The system and solutions are capable of recommending operational changes during drilling operations while the limiter occurs (referred to as a “founder point”). The limiter identification uses probability distributions to determine whether the incoming data stream falls outside of a specified estimated probability-distribution-significance level. An outlier in comparison with the probability distribution space may indicate a change in drilling conditions, allowing the driller to detect environmental changes periodically during drilling. Optimization Mechanism and Work Flows The relationship between ROP, DSE, and DOC creates three regions in any rock. As shown in Fig. 1, Region 2 is a highly effective cutting region; the other regions produce inadequate or excessive potential cutting performance. Tracing parameter deviation, lithology-change plots and limiters such as bit balling and vibrations can be identified in real time during drilling operations. Moreover, the parameters are updated in an optimal direction to maximize potential performance in line with Region 2.

Contributory Influence of Drill Cuttings on Equivalent Circulation Density Model in Deviated Wellbores

The estimation of equivalent circulation density (ECD) in oil well drilling and completion is rather of crucial importance and much care must be given in its calculation. This is because ECD being so sensitive, errors in its value estimation could lead to severe drilling and completion problems like kicks, loss circulation etc. especially when drilling in horizontal well sections, deepwater, depleted reservoirs, and wells with narrow pressure window. Traditional ECD calculation have only focused on the annular frictional pressure loss (AFPL) as the only contributory pressure loss (PL) in the ECD calculations, and most literatures have given more attention to this concept. Other factors aside AFPL contributes to the total PL at the bottom of the wellbore and these affect the value of ECD during drilling and completion operations. One of these factors is PL due to drill cuttings in the wellbore. In this work, the additional effect of drill cuttings to the annular frictional loss (AFL) in the wellbore has been considered. Awah BX2 well in the Niger Delta was used as case study. The Awah BX2 well is a deviated well that starts its inclination at 5000ft depth and having a measured depth of 14000ft. Mud of 8.8 ppg was used in the study. Matlab software was used in the model simulation. Emphasis was made on results from the mud with and without drill cuttings. Effects of ROP, mud flowrate, concentration of cuttings have been investigated to determine the ECD values and pressure losses in the wellbore. From the results, it was observed that the presence of cuttings in the mud increased pressure loss and hence the ECD. It was also observed from the analysis that increasing value of bit rate of penetration (ROP) increases the concentration of cuttings and hence the pressure loss and ECD for a particular mud flowrate but when the concentration of cuttings increases so much, the ROP decreased. Increase in mud flowrate decreases the effective solids density and hence decreases the ECD and pressure loss. The model utilized in the study more accurately predicts pressure losses and ECD than that traditionally used in ECD calculations.