Numerical Simulation Research on Cutting Rock with a PDC Cutter Assisted by an Impact Force

Extensive studies have been carried out on cutting rock with a PDC cutter, but cutting rock assisted by impact force is rarely studied. In this paper, cutting rock using conical and cylindrical PDC cutters assisted by impact force were researched with the explicit dynamic model. The laws of cutting rock using a cylindrical cutter assisted by impact force are the same as those of a conical cutter. There are thresholds of impact frequency and amplitude when they are single variables. When impact frequency is lower than the threshold frequency, the impact frequency is the dominant frequency in the frequency spectrum of weight on bit (WOB), and the amplitude of dominant frequency and removal volume decreases with the increase of impact frequency. When the impact frequency is higher than the threshold frequency, there is no dominant frequency in the frequency spectrum of WOB, and the removal volume behaves the same. When the impact force is lower than the threshold amplitude, there is no dominant frequency in the frequency spectrum of WOB, and it does not affect the removal volume but the removal volume is positively correlated with the impact amplitude. When the impact amplitude is higher than the threshold amplitude, the removal volume is also positively correlated with the impact amplitude, and the removal volume assisted by low-frequency (20 Hz and 40 Hz) impact force is higher. The frequency threshold and amplitude threshold of the conical cutter are smaller than those of the cylindrical cutter. Although the cutting depth and removal volume of the conical cutter are lower than those of the cylindrical cutter, the amplifications of cutting depth and removal volume of the conical cutter are higher than those of the cylindrical cutter when assisted by impact force.

A Real-Time Friction Prediction Model for in Service Drill String Based on Machine Learning Methods Coupling with Mechanical Mechanism Analysis

With highly deviated wells and horizontal wells are widely used in the oil industry. The large slope well sections and long horizontal well sections will lead to a sharp increase of the drill string torque and friction, which may reduce the drilling efficiency, and even lead to accidents. Therefore, real-time and accurate analysis of drill string’s torque and friction is an urgent problem facing by the modern drilling technology. The paper established a real-time friction prediction model that combines machine learning methods with drill string mechanical mechanism analysis model. Based on 84000 sets of field monitoring data obtained on-site, a regular data training set for weight on bit (WOB) and torque prediction was constructed with 23 types of time-series related parameters and 10 types of timing independent parameters. Relationships between time-series related parameters and timing independent parameters with the weight on bit and torque were trained to utilize long and short-term memory (LSTM) neural network and muti-layer back propagation (BP) network respectively. The new developed LSTM-BP neural network achieves high-precision prediction results of WOB and torque with a relative error of less than 14%. Based on derived WOB and torque prediction results, a theoretical mechanical analysis model of the entire drill string was adopted in this paper to develop the quantitative relation between WOB and torque with the friction coefficient of the drill string and oil casing. Suitable friction coefficients along the drill string can be finally obtained by solving the equilibrium function between predicted WOB, torque and measured hook load, rotary-table torque via an iteration algorithm. A case study was performed finally using the proposed intelligent analysis method to calculate the friction coefficients. This proposed methodology can be referenced to decrease the sticking risks and improve the drilling efficiency, which can finally increase the extension limit of horizontal wells in complex strata.

Micro-Testing While Drilling for Rate of Penetration Optimization: Experiments and Simulations

The Rate of Penetration (ROP) is one of the key parameters related to the efficiency of the drilling process. Within the confines of operational limits, the drilling parameters affecting the ROP should be optimized to drill more efficiently and safely, to reduce the overall cost of constructing the well. In this study, a data-driven optimization method called Extremum Seeking (ES) is employed to automatically find and maintain the optimal Weight on Bit (WOB) which maximizes the ROP. The ES algorithm is a model-free method which gathers information about the current downhole conditions by automatically performing small tests with the WOB and executing optimization actions based on the test results. In this paper, this optimization method is augmented with a combination of a predictive and a reactive constraint handling technique to adhere to operational limitations. These methods of constraint handling within ES application to drilling are demonstrated for a maximal limit imposed on the surface torque, but the methods are generic and can be applied on various drilling parameters. The proposed optimization scheme has been tested with experiments on a downscaled drilling rig and simulations on a high-fidelity drilling simulator of a full-scale drilling operation. The experiments and simulations show the method's ability to steer the system to the optimum and to handle constraints and noisy data, resulting in safe and efficient drilling at high ROP.

Combined Control Mechanism of Weight on Bit and Rate of Penetration with a Downhole Robot in the Coiled-Tubing Drilling Process

Summary Downhole robots were used to solve the problem of downhole tool transportation in an oil/gas horizontal well. However, current downhole robots do not control the weight on bit (WOB) and rate of penetration (ROP). This paper proposes the combined control method of WOB and ROP using an electric proportional overflow valve (EPOV) and an electric proportional throttle valve (EPTV). First, the mathematical model of the electrohydraulic control of the downhole robot is established. It is found that when the maximum pressure of the EPOV is greater than the differential pressure between the inner and outer of the downhole robot, the control parameters are drilling-fluid displacement and circulation area of the EPTV. When the maximum pressure of the EPOV is less than the differential pressure between the inner and outer of the downhole robot, the control parameters are drilling-fluid displacement, circulation area of the EPTV, and pressure of the EPOV. Moreover, it is found that the relationship of WOB and ROP in the combined control method is a surface rather than a line in a 2D coordinate. Therefore, the downhole robot can be adjusted while drilling at a stable ROP or a stable WOB. Finally, the combined control method of WOB and ROP with the downhole robot proposed in this paper was verified with an experiment. According to the experimental data, it is further found that an EPOV cannot only control WOB and ROP, but also can control the upper limit of WOB fluctuation. Thus, the control of WOB fluctuation can protect the bit from damage and prolong the life of the bit. This paper presents a foundation for the control of WOB and ROP with downhole robots. It has scientific and engineering significance for promoting downhole robots in drilling engineering.

Real-Time Solution for Down Hole Torque Estimation and Drilling Optimization in High Deviated Wells Using Artificial Intelligence

ABSTRACT This project provides a new realistic solution for the accuracy of down hole torque measurements using the integration of the Artificial intelligence (AI) technology with the downhole challenges being faced while drilling deep and high deviated wells. The new estimates are based on surface measurements which have the major influence on the bit torque (downhole torque) values while drilling. Artificial intelligence technology and its related applications such as; artificial neural network (ANN), support vector machine (SVM) and adaptive neuro fuzzy interference system (ANFIS) will be utilized to predict and estimate accurate wellbore torque which will be applied effectively to prevent real time stuck pipe situation through a friendly user software which will maintain the downhole torque within the SAFE zone by controlling the unified surface drilling variables such as; weight on bit (WOB), Rate of Penetration (ROP) and Flow Rate. This downhole torque model will be validated and verified through a real drilling scenario from a field in north of Africa. The field data includes weight on bit, surface torque, stand-pipe pressure, and rate of penetration were collected from the mentioned well which had experienced a costly stuck pipe situation. However, with the provided model the same encountered scenario will be avoided, due to the optimization of the real time drilling variables and hence, saving the well and evade a costly non-productive time.

The Development and Field Applications of Ultra-Deepwater Structural Conductor Jetting in Western South China Sea

Lingshui X-1 block is located in ultra-deepwater region in western South China Sea. Drilling in this area are encountering many technical problems, such as low temperature, poor lithology in shallow formation, low fracture pressure gradient, gas hydrate and shallow geological hazards, which bring great technical challenges to subsea wellhead stability (Yang et al., 2013). In order to ensure wellhead stability and improve top-hole operation efficiency, jetting technology was used for spud-in. First of all, carrying capacity curve of structural conductor was obtained from mechanics analysis of shallow seabed soil in Lingshui X-1 block. Secondly, structural conductor size selection and load analysis were carried out to determine safe setting depth of structural conductor in Lingshui X-1 block. Finally, bit stick-out, bit size selection, Weight on Bit (WOB) and pump rate were optimized on the basis of comprehensive analysis of ultra-deepwater under top-hole jetting technology and BHA characteristics. Well LSX-1-1 was taken as an example to illustrate field operation for top-hole jetting. This successful case of top-hole jetting technology in Lingshui X-1 block of western South China Sea could provide technical guidance for future drilling activity in similar ultra-deepwater wells.

Deployment of Downhole Mechanics Measurement System and Drilling Dynamics Modelling to Enhance Overall Drilling Performance Under Complete Mud Losses Environment

Drilling surface 16-in. and 12.25-in. sections in Middle East often accomplished by complete mud losses where downhole dynamic changed completely. To increase the performance and reduce drilling time the Positive Displace Motors (PDM) are used, however drilling under complete mud losses scenario may lead to a failure of the PDM, Measure While Drilling (MWD) tool, jar and any other components of the Bottom Hole Assembly (BHA). This manuscript describes the study of BHA dynamic in total loss scenario aiming to increase Rate of penetration (ROP) and decrease mechanical failures. The changing in drilling dynamics under complete mud losses increases the severity of shock and vibrations (S&V), BHA whirl and, consequently, leads to downhole failures. Local practices have been used to control this risk by taking an over conservative approach, limiting Weight on Bit (WOB) and Revolution per Minute (RPM) to very low levels, affecting overall performance. To comprehensively understand the level of shock and vibrations under complete mud losses based on the modeled data, a Downhole Mechanics Measurement (DMM) system was used in the BHA to acquire the required data in real time to confirm and further improve the modeling of drilling dynamics. A drilling schedule with several combinations of WOB and RPM was developed to cover the full drilling envelop. This study provided valuable understanding on the drilling dynamics while drilling under complete mud losses and allowed to clearly define the limiting boundaries to optimize ROP without jeopardizing the mechanical integrity of the BHA, particularly the PDM and drilling jar. On each formation drilled, RPM, WOB were changed to cover all possible combinations and, using the continuous real time measurement, ROP was optimized based on the level of shocks and vibrations experienced. Furthermore, the recorded mode Low and High-frequency data enabled to model the drilling dynamics and to quantify the effects of shocks and vibrations on the BHA. As a result, the wells have been drilled with significant ROP improvement (saving one day per run) and without downhole failures, achieving higher than expected performance results.

Estimating Formation Tops while Drilling Using Rate of Penetration ROP and Mechanical Specific Energy MSE

Accurate determination of formation tops while drilling is a critical part of exploration geology workflow. Operational decisions on coring, wireline logging, casing, and final well depth largely depend on it. One of the commonly used methods for picking formation tops while drilling is to correlate the rate of penetration (ROP) of the new well to wireline logs from offset wells where there is no logging while drilling (LWD) data. Picking formation tops based on only ROP from a new well can result in picking the wrong formation tops. To improve the workflow and outcome, this paper proposes the combination of ROP and Mechanical Specific Energy (MSE) for estimating formation tops while drilling. MSE is a measure of the energy required to crush or drill through a unit volume of rock. Because MSE is related to rock strength, it can be correlated to changes in lithofacies and formation tops. There are three key steps necessary for utilizing mechanical specific energy to estimate formation tops. First, select the input drilling data relevant to the applicable MSE equation. There are several empirical equations in the literature which can be used for estimating MSE. Input data are ROP, Weight on Bit (WOB), Bit Size (BS), Rotation Per Minute (RPM), and Torque (TORQ) from both the offset wells and the new well. Second, utilize a predetermined empirical equation to estimate MSE. Third, correlate MSE and ROP from the new well to both MSE, ROP, and wireline logs from offset wells (where available) to determine formation tops in the new well. Application of the proposed workflow to two wells show 1) distinct bed boundaries, which agree with formation tops picked using wireline logs; (2) that including MSE increases confidence and reliability of the data and makes it easy to identify the different formation boundaries based on the observed features of both MSE and ROP in the new well; and (3) that MSE variations are sensitive to formation strength, which may indicate rock mechanical changes and formation heterogeneity. This paper presents an alternative method of picking formation tops using MSE and ROP while drilling. The preliminary results based on the two test wells showed over 95% match with those picked using wireline logs of the same new well. As a result, this workflow enhances the ability of geoscientists to correlate subsurface geological features, reduces the uncertainty associated with picking formation tops, casing, and coring depths. Furthermore, it improves the confidence in the result, enhances the quality of operational decisions, and reduces the non-productive time (NPT) and well-cost.