A Tool for Derivation of Real Time Lithological Information from Drill Bit Sound

Abstract Real time lithological information at the drill bit is required for some important drilling operations, such as geo-steering and casing shoe positioning. This paper presents a novel tool "Petro-phone" for recording and processing drill bit sounds, which are generated by the drill bit cutting the rock, in order to provide real time lithological information for the rock at the drill bit. A prototype and a preliminary professional version of Petro-phone have been developed and field trialed. Petro-phone is a surface tool with its acoustic sensors attached to the top drive of a drill rig at some strategical locations for maximally picking up drill bit sounds. The drill bit sounds generated at the drill bit transmit along drill string and drive shaft to reach to the acoustic sensors. Since all the parts along the drill bit sound transmission pathway are made of steel, the drill bit sounds transmit efficiently from the source (drill bit) to the sensors. Preliminary results from two field trials show that drill bit sound patterns correlate with lithologies. The results also indicate that a parameter "Apparent Power" of drill bit sounds negatively correlates with gamma log. Due to its true real time nature, Petro-phone potentially has some real time applications, such as geo-steering, casing shoes positioning. Recorded drill bit sound can also potentially be used to derive lithological information, such as lithology type.

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Study of stick–slip suppression and robustness to parametric uncertainty in drill strings containing torsional vibration tool using sliding-mode control

Proceedings of the Institution of Mechanical Engineers Part K Journal of Multi-body Dynamics ◽

10.1177/14644193211045273 ◽

2021 ◽

pp. 146441932110452

Author(s):

Jialin Tian ◽

Jie Wang ◽

Siqi Zhou ◽

Yinglin Yang ◽

Liming Dai

Keyword(s):

Torsional Vibration ◽

Complex Dynamics ◽

Sliding Mode ◽

Parametric Uncertainty ◽

Drill String ◽

Lumped Parameter Model ◽

Drilling Process ◽

Drill Bit ◽

Stick Slip ◽

Drilling Operations

Excessive stick–slip vibration of drill strings can cause inefficiency and unsafety of drilling operations. To suppress the stick–slip vibration that occurred during the downhole drilling process, a drill string torsional vibration system considering the torsional vibration tool has been proposed on the basis of the 4-degree of freedom lumped-parameter model. In the design of the model, the tool is approximated by a simple torsional pendulum that brings impact torque to the drill bit. Furthermore, two sliding mode controllers, U1 and U2, are used to suppress stick–slip vibrations while enabling the drill bit to track the desired angular velocity. Aiming at parameter uncertainty and system instability in the drilling operations, a parameter adaptation law is added to the sliding mode controller U2. Finally, the suppression effects of stick–slip and robustness of parametric uncertainty about the two proposed controllers are demonstrated and compared by simulation and field test results. This paper provides a reference for the suppression of stick–slip vibration and the further study of the complex dynamics of the drill string.

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Improved Drilling Operations with Wired Drill Pipe and Along-String Measurements – Learnings and Highlights from Multiple North Sea Deployments

10.2118/204029-ms ◽

2021 ◽

Author(s):

Børge Engdal Nygård ◽

Espen Andreassen ◽

Jørn Andre Carlsen ◽

Gunn Åshild Ulfsnes ◽

Steinar Øksenvåg ◽

...

Keyword(s):

Continental Shelf ◽

Real Time ◽

High Speed ◽

Drill Pipe ◽

Large Data ◽

Drill String ◽

Bottom Hole Assembly ◽

Drilling Operations ◽

Downhole Measurements ◽

Remote Operations

Abstract Over the last few years, multiple wells have been drilled in the Norwegian Continental Shelf (NCS) and the United Kingdom Continental Shelf (UKCS) using wired drill pipe (WDP). This paper captures highlights from using real-time downhole measurements provided by WDP, for improved drilling operations. It presents learnings on how WDP measurements have been used in the operator's decision process. As part of WDP, along-string measurement subs (ASM) are equipped with temperature, annular/internal pressure, rotation and vibrations sensors. Data is transmitted to surface at high speed and is available in real-time, even when flow is off. The data provide great insight into the hole conditions along the drill string and at the bottom hole assembly (BHA). Based on this insight, drilling parameters at surface can be accurately adjusted, resulting in increased overall efficiency. Large data amounts can be communicated to and from surface with negligible time delay and independent from fluid circulation. Displaying the downhole measurements in real-time, both at the rig site and in remote operations centers has proven essential when optimising well construction activities. All parties need to access the same information in real-time. Moreover, the data need to be presented in an intuitive manner that enable improved operational decisions. To maximize WDP values, the Operator has learned that downhole data must be used to adjust drilling operations in real-time.

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Seismic-while-drilling applications from the first DrillCAM trial with wireless geophones and instrumented top drive

The Leading Edge ◽

10.1190/tle39060422.1 ◽

2020 ◽

Vol 39 (6) ◽

pp. 422-429

Author(s):

Andrey Bakulin ◽

Ali Aldawood ◽

Ilya Silvestrov ◽

Emad Hemyari ◽

Flavio Poletto

Keyword(s):

Real Time ◽

Polycrystalline Diamond ◽

Drill String ◽

Sensor Data ◽

Continuous Data ◽

Near Surface ◽

Initial Application ◽

Look Ahead ◽

Drilling Operations ◽

Single Sensor

Advanced geophysical sensing while drilling is being driven by trends to automate and optimize drilling and the desire to better characterize complex near surface and overburden in desert environments. We introduce the DrillCAM system, which combines a set of geophysical techniques from seismic while drilling (SWD), drill-string vibration health, estimation of formation properties at the bit, and imaging ahead of and around the bit. We present data acquisition, processing, and initial application results from the first field trial on an onshore well in a desert environment. In this study, we focus on SWD applications. For the first time, wireless geophones installed around a rig were used to acquire continuous data while drilling. We demonstrate the feasibility of such a system to provide flexible acquisition geometries that are easily expandable with increasing bit depth without interference from drilling operations. Using a top-drive sensor as a pilot, we transform the drill-bit noise into meaningful and reliable seismic signals. The data were used to retrieve a check shot while drilling, make kinematic look-ahead predictions, and obtain a vertical seismic profiling corridor stack matching surface seismic. Robust near-offset check-shot signals were received from roller-cone and polycrystalline diamond compact (PDC) bits above 7200 ft after limited preprocessing of challenging single-sensor data with supergrouping. Detecting signals from deeper sections drilled with PDC bits may require more advanced processing by using an entire 2D spread of wireless geophones and downhole pilots. The real-time capabilities of the system make the data available for continuous data processing and interpretation that will facilitate drilling automation and improve real-time decision making.

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Predicting Dysfunction Vibration Events while Drilling Using LSTM Recurrent Neural Networks

10.2118/205571-ms ◽

2021 ◽

Author(s):

Narendra Vishnumolakala ◽

Dean Michael Murphy ◽

Thu Nguyen ◽

Enrique Zarate Losoya ◽

Vivekvardhan Reddy Kesireddy ◽

...

Keyword(s):

Real Time ◽

Short Term Memory ◽

Warning System ◽

Complex Problem ◽

Drill String ◽

Sequential Data ◽

Look Ahead ◽

Drilling Data ◽

The Future ◽

Drilling Operations

Abstract The objective of the study is to build a robust Recurrent Neural Network system using Long-Short-Term-Memory (LSTM) to predict future vibrations during drilling operations. This provides a reliable solution to the complex problem of modeling several forms of vibrations encountered downhole. This accurate prediction system can be readily integrated into advisory/warning systems giving drillers the potential to save time, improve safety, and increase efficiency in drilling operations. High-frequency downhole drilling data onshore fields, obtained from a major O&G service provider, was used to train and validate the models. First, multiple classification algorithms such as Logistic Regression, KNN, Decision Trees, Random Forest were utilized to identify the presence and severity of Stickslip, Whirl, and other drill-string vibrations. LSTM-RNN was then used instead of traditional RNN intended for sequential data, to resolve the vanishing gradient problem. LSTM-RNN architecture was built to predict vibrations a)10 seconds and b) 30 seconds into the future. Results of the traditional classification models confirmed the hypothesis that dysfunctions can be successfully identified based on real-time downhole drilling data. 98% accuracy was obtained in successfully identifying torsional vibrations during drilling. A total of 101 parameters including measured and derived variables are available in the dataset. Modeling was performed with 14 features and vibrations were predicted. The RNN model was trained on data from multiple wells that encountered vibrations during drilling. The models were able to predict vibrations 10 seconds into the future with an MSE of 0.02 and 30 seconds into the future with reasonable accuracy and MSE of 0.10. Avoiding excessive vibrations will result in fewer trips by increasing longevity and reducing malfunctions of downhole electronics, the drill-string, and the BHA. Reduced NPT means drilling complex wells efficiently in less time which in turn directly translates to lower costs for the company. In addition to significant cost benefits, automated technology predicting anomalies and reacting in real-time translates to improved safety because it would now require fewer operators at risk on the rig floor. The work opens up avenues for a sophisticated advisory/warning system and effective ‘look-ahead’ drilling processes in the future.

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DRILL BIT SEISMIC—DRILLING OPTIMISATION CASE STUDY: CRUX–1

The APPEA Journal ◽

10.1071/aj00032 ◽

2001 ◽

Vol 41 (1) ◽

pp. 623

Author(s):

H. Cao ◽

Y. Kurata

Keyword(s):

Real Time ◽

Cost Savings ◽

Drill String ◽

Acoustic Energy ◽

Depth Information ◽

Drilling Process ◽

Drill Bit ◽

Travel Times ◽

Velocity Information

Drill Bit Seismic (DBSeis) technique utilises the acoustic energy generated during the drilling process to provide vital information about the subsurface structure. This information, produced in real time at the wellsite, is used to optimise the drilling process, leading to significant cost savings and enhanced safety.When a working drill bit destroys the rock at the bottom of the hole, it radiates acoustic energy into the surrounding formation. This acoustic energy is recorded by sensors both at the top of the drill-string and placed on the sea floor in the vicinity of the rig. Travel times recorded by the sensors on the ground are corrected for drill-string travel times to provide the time-depth information. This accurate time-depth information can then be used to continuously update the depth of drilling hazards by converting the surface seismic markers from time into depth domain.After experiencing excessive loss of circulation in the Johnson Formation in a nearby well, DBSeis was run in the Crux–1 well to help predict the depth of the top Johnson Formation while drilling to the 13 3/8” casing shoe depth. The well program called for the casing shoe to be set as close to, but above this formation. The two way time of the Johnson formation had been estimated from the surface seismic to be 0.994 s. DBSeis was used to provide real time time-depth information to convert the two way time to depth.The estimated top Johnson Formation at 0.994 s two way time (TWT) corresponded to a depth of 1,231 m SS using pre-drill velocity information. Using the DBSeis time-depth data, this depth was reduced to 1,192 m SS and the casing shoe was set at 1,164 m SS. The actual depth of the top Johnson Formation was later estimated at 1,178 m SS from ROP/WOB.

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