Dynamic Measurement of Spatial Attitude at Bottom Rotating Drillstring: Simulation, Experimental, and Field Test

2015 ◽  
Vol 138 (2) ◽  
Author(s):  
Qilong Xue ◽  
Ruihe Wang ◽  
Baolin Liu ◽  
Leilei Huang
Keyword(s):  
Real Time ◽  
Measurement Errors ◽  
Time Window ◽  
Measurement Data ◽  
Movement Patterns ◽  
Dynamic Measurement ◽  
Drilling Process ◽  
Stick Slip ◽  
Actual Measurement ◽  
Gas Drilling

In the oil and gas drilling engineering, measurement-while-drilling (MWD) system is usually used to provide real-time monitoring of the position and orientation of the bottom hole. Particularly in the rotary steerable drilling technology and application, it is a challenge to measure the spatial attitude of the bottom drillstring accurately in real time while the drillstring is rotating. A set of “strap-down” measurement system was developed in this paper. The triaxial accelerometer and triaxial fluxgate were installed near the bit, and real-time inclination and azimuth can be measured while the drillstring is rotating. Furthermore, the mathematical model of the continuous measurement was established during drilling. The real-time signals of the accelerometer and the fluxgate sensors are processed and analyzed in a time window, and the movement patterns of the drilling bit will be observed, such as stationary, uniform rotation, and stick–slip. Different signal processing methods will be used for different movement patterns. Additionally, a scientific approach was put forward to improve the solver accuracy benefit from the use of stick–slip vibration phenomenon. We also developed the Kalman filter (KF) to improve the solver accuracy. The actual measurement data through drilling process verify that the algorithm proposed in this paper is reliable and effective and the dynamic measurement errors of inclination and azimuth are effectively reduced.

New LWD Image Improvement Method to Mitigate Interpretation Risks

2021 ◽  
Author(s):  
Tianhua Zhang ◽  
Shiduo Yang ◽  
Chandramani Shrivastava ◽  
Adrian A ◽  
Nadege Bize-Forest
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Best Practice ◽  
Synthetic Data ◽  
Image Resolution ◽  
Drilling Process ◽  
Drilling Tool ◽  
Stick Slip ◽  
Geological Interpretation ◽  
Wellbore Temperature

Abstract With the advancement of LWD (Logging While Drilling) hardware and acquisition, the imaging technology becomes not only an indispensable part of the drilling tool string, but also the image resolution increases to map layers and heterogeneity features down to less than 5mm scale. This shortens the geological interpretation turn-around time from wireline logging time (hours to days after drilling) to semi-real time (drilling time or hours after drilling). At the same time, drilling motion is complex. The depth tracking is on the surface referenced to the surface block movement. The imaging sensor located downhole can be thousands of feet away from the surface. Mechanical torque and drag, wellbore friction, wellbore temperature and weight on bit can make the downhole sensor movement motion not synchronized with surface pipe depth. This will cause time- depth conversion step generate image artifacts that either stop real-time interpretation of geological features or mis-interpret features on high resolution images. In this paper, we present several LWD images featuring distortion mechanism during the drilling process using synthetic data. We investigated how heave, depth reset and downhole sensor stick/slip caused image distortions. We provide solutions based on downhole sensor pseudo velocity computation to minimize the image distortion. The best practice in using Savitsky-Golay filter are presented in the discussion sections. Finally, some high-resolution LWD images distorted with drilling-related artifacts and processed ones are shown to demonstrate the importance of image post-processing. With the proper processed images, we can minimize interpretation risks and make drilling decisions with more confidence.

scholarly journals Neural network approach to reduce dynamic measurement errors

ACTA IMEKO ◽  
2016 ◽  
Vol 5 (3) ◽  
pp. 24 ◽  
Author(s):  
Andrei Sergeevich Volosnikov ◽  
Aleksandr L. Shestakov
Keyword(s):  
Neural Network ◽  
Measurement Errors ◽  
Measurement Data ◽  
Dynamic Measurement ◽  
Network Approach ◽  
Neural Network Approach ◽  
Experimental Data Processing ◽  
The Neural Network ◽  
Mathematical Processing ◽  
Processing Of Measurement Data

<p>The neural network inverse model of a sensor with filtration of the sequentially recovered signal is considered. This model effectively reduces the dynamic measurement errors due to deep mathematical processing of measurement data. The result of the experimental data processing of a dynamic temperature measurement validates the efficiency of the proposed neural network approach to reduce dynamic measurement errors.</p>

Inline Drilling Fluid Property Measurement, Integration, and Modeling to Enhance Drilling Practice and Support Drilling Automation

2021 ◽  
Author(s):  
Sanjit Roy ◽  
Saiyid Z. Kamal ◽  
Richard Frazier ◽  
Ross Bruns ◽  
Yahia Ait Hamlat
Keyword(s):  
Real Time ◽  
Drilling Fluid ◽  
Measurement Data ◽  
Lessons Learned ◽  
Valuable Insight ◽  
Drilling Process ◽  
Time Data ◽  
Fluid Property ◽  
Real Time Data ◽  
Fluid Properties

Abstract Frequent, reliable, and repeatable measurements are key to the evolution of digitization of drilling information and drilling automation. While advances have been made in automating the drilling process and the use of sophisticated engineering models, machine learning techniques to optimize the process, and lack of real-time data on drilling fluid properties has long been recognized as a limiting factor. Drilling fluids play a significant function in ensuring quality well construction and completion, and in-time measurements of relevant fluid properties are key to automation and enhancing decision making that directly impacts well operations. This paper discusses the development and application of a suite of automated fluid measurement devices that collect key fluid properties used to monitor fluid performance and drive engineering analyses without human involvement. The deployed skid-mounted devices continually and reliably measure properties such as mud weight, apparent viscosity, rheology profiles, temperatures, and emulsion stability to provide valuable insight on the current state of the fluid. Real-time data is shared with relevant rig and office- based personnel to enable process monitoring and trigger operational changes. It feeds into real-time engineering analyses tools and models to monitor performance and provides instantaneous feedback on downhole fluid behavior and impact on drilling performance based on current drilling and drilling fluid property data. Equipment reliability has been documented and demonstrated on over 30 wells and more than 400 thousand ft of lateral sections in unconventional shale drilling in the US. We will share our experience with measurement, data quality and reliability. We will also share aspects of integrating various data components at disparate time intervals into real-time engineering analyses to show how real-time measurements improve the prediction of well and wellbore integrity in ongoing drilling operations. In addition, we will discuss lessons learned from our experience, further enhancements to broaden the scope, and the integration with operators, service companies and other original equipment manufacturer in the domain to support and enhance the digital drilling ecosystem.

Evaluation of Derived Controllable Variables for Predicting Rop Using Artificial Intelligence in Autonomous Downhole Rotary Drilling System

2021 ◽  
Author(s):  
Kingsley Williams Amadi ◽  
Ibiye Iyalla ◽  
Yang Liu ◽  
Mortadha Alsaba ◽  
Durdica Kuten
Keyword(s):  
Real Time ◽  
Specific Energy ◽  
Penetration Rate ◽  
Drilling Process ◽  
Stick Slip ◽  
Conservation Of Energy ◽  
Rate Of Penetration ◽  
Mechanical Specific Energy ◽  
Drilling Parameters ◽  
Drilling System

Abstract Fossil fuel energy dominate the world energy mix and plays a fundamental role in our economy and lifestyle. Drilling of wellbore is the only proven method to extract the hydrocarbon reserves, an operation which is both highly hazardous and capital intensive. To optimize the drilling operations, developing a high fidelity autonomous downhole drilling system that is self-optimizing using real-time drilling parameters and able to precisely predict the optimal rate of penetration is essential. Optimizing the input parameters; surface weight on bit (WOB), and rotary speed (RPM) which in turns improves drilling performance and reduces well delivery cost is not trivial due to the complexity of the non-linear bit-rock interactions and changing formation characteristics. However, application of derived variables shows potential to predict rate of penetration and determine the most influential parameters in a drilling process. In this study the use of derived controllable variables calculated from the drilling inputs parameters were evaluated for potential applicability in predicting penetration rate in autonomous downhole drilling system using the artificial neutral network and compared with predictions of actual input drilling parameters; (WOB, RPM). First, a detailed analysis of actual rock drilling data was performed and applied in understanding the relationship between these derived variables and penetration rate enabling the identification of patterns which predicts the occurrence of phenomena that affects the drilling process. Second, the physical law of conservation of energy using drilling mechanical specific energy (DMSE) defined as energy required to remove a unit volume of rock was applied to measure the efficiency of input energy in the drilling system, in combination with penetration rate per unit revolution and penetration rate per unit weight applied (feed thrust) are used to effective predict optimum penetration rate, enabling an adaptive strategize which optimize drilling rate whilst suppressing stick-slip. The derived controllable variable included mechanical specific energy, depth of cut and feed thrust are calculated from the real- time drilling parameters. Artificial Neutral Networks (ANNs) was used to predict ROP using both input drilling parameters (WOB, RPM) and derived controllable variables (MSE, FET) using same network functionality and model results compared. Results showed that derived controllable variable gave higher prediction accuracy when compared with the model performance assessment criteria commonly used in engineering analysis including the correlation coefficient (R2) and root mean square error (RMSE). The key contribution of this study when compared to the previous researches is that it introduced the concept of derived controllable variables with established relationship with both ROP and stick-slip which has an advantage of optimizing the drilling parameters by predicting optimal penetration rate at reduced stick-slip which is essential in achieving an autonomous drilling system. :

Developing ultrasonic soft sensors to measure rheological properties of non-Newtonian drilling fluids

2019 ◽  
Vol 86 (12) ◽  
pp. 744-757
Author(s):  
Morten Hansen Jondahl ◽  
Håkon Viumdal
Keyword(s):  
Machine Learning ◽  
Rheological Properties ◽  
Real Time ◽  
Drilling Fluids ◽  
Drilling Process ◽  
Soft Sensors ◽  
Gas Drilling ◽  
Fluid Systems ◽  
Machine Learning Model ◽  
Ultrasonic Measurements

AbstractSurveillance of the rheological properties of drilling fluids is crucial when drilling oil wells. The prevailing standard is lab analysis. The need for automated real-time measurements is, however, clear.Ultrasonic measurements in non-Newtonian fluids have been shown to exhibit a non-linear relationship between the acoustic attenuation and rheological properties of the fluids. In this paper, three different fluid systems are examined. They are diluted to give a total of 33 fluid sets and their ultrasonic and rheological properties are measured. Machine learning models are applied to develop soft sensors that are capable of estimating the rheological properties based on the ultrasonic measurements. This study explores three different machine learning model types and, extensive training and tuning of the models is carried out. The best model types that show good results and the potential to develop a real-time sensor system suitable for use in oil & gas drilling process automation are selected.

scholarly journals Application of an innovative ridge-ladder-shaped polycrystalline diamond compact cutter to reduce vibration and improve drilling speed

2020 ◽  
Vol 103 (3) ◽  
pp. 003685042093097
Author(s):  
Dou Xie ◽  
Zhiqiang Huang ◽  
Yuqi Yan ◽  
Yachao Ma ◽  
Yuan Yuan
Keyword(s):  
Oil And Gas ◽  
Polycrystalline Diamond ◽  
Rock Breaking ◽  
Drilling Process ◽  
Drilling Speed ◽  
Stick Slip ◽  
Gas Drilling ◽  
Drill Bits ◽  
Element Simulation ◽  
Polycrystalline Diamond Compact

Polycrystalline diamond compact bits have been widely used in the Oil and Gas drilling industry, despite the fact that they may introduce undesired vibration into the drilling process, for example, stick-slip and bit bounce, which accelerate the failure rate and lead to higher drilling costs. First, we develop an innovative ridge-ladder-shaped polycrystalline diamond compact cutter, which has ridge-shaped cutting faces and multiple cutting edges with stepped distribution, in the hope of reducing vibration and improving drilling speed. Then, the scrape tests of ridge-ladder-shaped and general polycrystalline diamond compact cutters are carried out in a laboratory, indicating that the cutting, lateral, and longitudinal forces on ridge-ladder-shaped polycrystalline diamond compact cutters are smaller and with minor fluctuations. Due to different rock-breaking mechanisms, ridge-ladder-shaped polycrystalline diamond compact cutters have higher cutting efficiency compared to general polycrystalline diamond compact cutters, which is also verified experimentally. Finally, the drilling characteristics of a new polycrystalline diamond compact bit fitted with some ridge-ladder-shaped polycrystalline diamond compact cutters are compared to those of a general polycrystalline diamond compact bit by means of finite element simulation. The results show that introducing ridge-ladder-shaped polycrystalline diamond compact cutters can not only reduce the stick-slip vibration, bit bounce, and backward rotation of drill bits effectively, but also improve their rate of penetration.

scholarly journals Method of Real-Time Wellbore Surface Reconstruction Based on Spiral Contour

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 291
Author(s):  
Hongqiang Li ◽  
Ruihe Wang
Keyword(s):  
Surface Structure ◽  
Real Time ◽  
Surface Reconstruction ◽  
Three Dimensional ◽  
Measurement Data ◽  
Surface Profile ◽  
Contour Line ◽  
Actual Measurement ◽  
Iterative Interpolation ◽  
Reconstructed Surface

A wellbore surface is an irregular surface structure. The distribution of points on the wellbore surface measured based on the drilling diameter is not uniform. Thus, the conventional modeling method based on a point cloud cannot satisfy the needs of real-time measurement updating and wellbore display. This study proposes a spiral profile method for drilling shaft surface reconstruction. Scattered data along the drilling diameter are measured, and an inverse distance weighting cylindrical space surface algorithm with iterative interpolation is used to obtain the spiral angle and pitch of a relatively homogeneous helical contour line along the surface of the shaft. Using sets of four adjacent points in the spiral, quadrilaterals are formed, and then all obtained quadrilaterals are used to form the wellbore inner surface structure. This method can further construct the outer surface spiral contour line to advance the quadrilateral surface to the spatial hexahedron structure. The caliper and gamma measurement data obtained from the calibrated wellbore were used to verify the real-time surface reconstruction and fusion while drilling. The homogenized reconstructed surface profile is more than 99.5% similar to the actual measurement. Proved by experiment and application, this method has very high real-time performance, and the three-dimensional stereo imaging wellbore with additional gamma attributes has good visual effects.

Offset Data Analysis and Seam Less Execution Through Real Time Monitoring Results in Step Change in Drilling Performance

2021 ◽  
Author(s):  
Singh Anurag Yadav ◽  
Imran Muhammad Chohan
Keyword(s):  
Real Time ◽  
Step Change ◽  
Management Tool ◽  
Oil Well ◽  
Optimization Approach ◽  
Real Time Monitoring ◽  
Stick Slip ◽  
Gas Drilling ◽  
Drilling Performance ◽  
Bottom Hole

Abstract In oil and gas drilling, consistency of performance delivery heavily depends upon rig capability and its ability to maintain performance assurance through its execution cycle. It's not an uncommon occurrence that a rig is found with an underperforming top drive, one such scenario was observed in an in-fill oil well drilling project. This project was essentially drilling horizontal wells with bottom hole assemblies which had primary drive mechanism as a top drive. The rig in question was struggling to provide not only the requisite RPM but also not been able to deliver consistent torque needed to drill the well. This study analyzes how severe rig limitations were overcome through an optimization plan in which most optimal BHA was designed and drilling practices were customized for safe and successful execution of wells. In order to understand root cause of the challenge, an offset well analysis was conducted, it identified that high torque was mostly generated while drilling through inter-bedded formations which typically caused top drive to stall. In addition, multiple tool failures were encountered due to the high stick slip which rig couldn't mitigate due to the low RPM yield of the top drive. To manage the rpm and torque limitations, a motorized RSS BHA was designed as a solution. Further, based on micro-stall events of motor only BHA's across the inter-bedded formations in the field, a stick slip management tool was placed below the motor so that a potential twist-off and/or motor damages can be avoided. Also, different bottom hole assembly's drilling dynamics response were analyzed to come up with optimal stabilization and connection practices to avoid back reaming while trip outs. This paper would showcase actual results which highlight improvements achieved in stagnant drilling performance of the project. The analysis would demonstrate how multiple wells were drilled in one run following the risk assessment developed from the optimization study and subsequent real time monitoring of mitigating actions while execution. The comprehensive bottoms-up drilling optimization approach helped save 4 planned days for each well, this really paves way to pursue applied-engineering solutions to achieve step change in drilling performances, especially on rigs which are severely limited either due to capacity or malperformance issues. The bottoms up approach taken to understand the drilling challenges followed by a methodical approach to address each of the challenges demonstrate importance of effective pre-job planning. Learnings from this study can be adopted as a template to mitigate similar drilling challenges.

Evaluation Method for Measurement Uncertainty of Antenna Surface Accuracy

2011 ◽  
Vol 105-107 ◽  
pp. 2063-2068
Author(s):  
Gan Li ◽  
Zong Chun Li ◽  
Shu Lu
Keyword(s):  
Coordinate System ◽  
Measurement Errors ◽  
Evaluation Method ◽  
Measurement Data ◽  
Simulation Method ◽  
Actual Measurement ◽  
Evaluation Indexes ◽  
Data Process ◽  
Surface Accuracy ◽  
Antenna Surface

This paper describes the basic data process of antenna surface geometrical measurement and the quality evaluation indexes, which are surface accuracy and its uncertainty.The peak to peak value of normal deviation is used to characterize the surface accuracy,and its deviation is defined as its uncertainty.The measurement errors are given under repeated measuring conditions.Under repeated measuring conditions,the simulation method is that adding the measurement errors calculated by repeated measurement to theoretical coordinates.Under single measuring conditions, the first step is to convert the measurement data from the measuring coordinate system to the design coordinate system to get the transformation parameters;then use these parameters to convert theoretical coordinates to the measurement coordinate system;and then add measurement errors to transformed coordinates for simulation.The key point is adding measurement errors to the data which do not contain measurement errors.The simulation and actual measurement experiments of a Φ0.7 meter antenna were conducted,which showed that the method is correct.

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