Probabilistic Real-Time Trajectory Control Considering Uncertainties of Drilling Parameters and Rock Properties

Author(s):  
Zhengchun Liu ◽  
Robello Samuel
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sherif M. Hanafy ◽  
Hussein Hoteit ◽  
Jing Li ◽  
Gerard T. Schuster

AbstractResults are presented for real-time seismic imaging of subsurface fluid flow by parsimonious refraction and surface-wave interferometry. Each subsurface velocity image inverted from time-lapse seismic data only requires several minutes of recording time, which is less than the time-scale of the fluid-induced changes in the rock properties. In this sense this is real-time imaging. The images are P-velocity tomograms inverted from the first-arrival times and the S-velocity tomograms inverted from dispersion curves. Compared to conventional seismic imaging, parsimonious interferometry reduces the recording time and increases the temporal resolution of time-lapse seismic images by more than an order-of-magnitude. In our seismic experiment, we recorded 90 sparse data sets over 4.5 h while injecting 12-tons of water into a sand dune. Results show that the percolation of water is mostly along layered boundaries down to a depth of a few meters, which is consistent with our 3D computational fluid flow simulations and laboratory experiments. The significance of parsimonious interferometry is that it provides more than an order-of-magnitude increase of temporal resolution in time-lapse seismic imaging. We believe that real-time seismic imaging will have important applications for non-destructive characterization in environmental, biomedical, and subsurface imaging.


Author(s):  
Valeria Artale ◽  
Mario Collotta ◽  
Cristina Milazzo ◽  
Giovanni Pau ◽  
Angela Ricciardello
Keyword(s):  

2021 ◽  
Author(s):  
Ahmed Al-Sabaa ◽  
Hany Gamal ◽  
Salaheldin Elkatatny

Abstract The formation porosity of drilled rock is an important parameter that determines the formation storage capacity. The common industrial technique for rock porosity acquisition is through the downhole logging tool. Usually logging while drilling, or wireline porosity logging provides a complete porosity log for the section of interest, however, the operational constraints for the logging tool might preclude the logging job, in addition to the job cost. The objective of this study is to provide an intelligent prediction model to predict the porosity from the drilling parameters. Artificial neural network (ANN) is a tool of artificial intelligence (AI) and it was employed in this study to build the porosity prediction model based on the drilling parameters as the weight on bit (WOB), drill string rotating-speed (RS), drilling torque (T), stand-pipe pressure (SPP), mud pumping rate (Q). The novel contribution of this study is to provide a rock porosity model for complex lithology formations using drilling parameters in real-time. The model was built using 2,700 data points from well (A) with 74:26 training to testing ratio. Many sensitivity analyses were performed to optimize the ANN model. The model was validated using unseen data set (1,000 data points) of Well (B), which is located in the same field and drilled across the same complex lithology. The results showed the high performance for the model either for training and testing or validation processes. The overall accuracy for the model was determined in terms of correlation coefficient (R) and average absolute percentage error (AAPE). Overall, R was higher than 0.91 and AAPE was less than 6.1 % for the model building and validation. Predicting the rock porosity while drilling in real-time will save the logging cost, and besides, will provide a guide for the formation storage capacity and interpretation analysis.


2021 ◽  
Author(s):  
Temirlan Zhekenov ◽  
Artem Nechaev ◽  
Kamilla Chettykbayeva ◽  
Alexey Zinovyev ◽  
German Sardarov ◽  
...  

SUMMARY Researchers base their analysis on basic drilling parameters obtained during mud logging and demonstrate impressive results. However, due to limitations imposed by data quality often present during drilling, those solutions often tend to lose their stability and high levels of predictivity. In this work, the concept of hybrid modeling was introduced which allows to integrate the analytical correlations with algorithms of machine learning for obtaining stable solutions consistent from one data set to another.


2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Abdulmalek Ahmed ◽  
Salaheldin Elkatatny ◽  
Abdulwahab Ali ◽  
Mahmoud Abughaban ◽  
Abdulazeez Abdulraheem

Drilling a high-pressure, high-temperature (HPHT) well involves many difficulties and challenges. One of the greatest difficulties is the loss of circulation. Almost 40% of the drilling cost is attributed to the drilling fluid, so the loss of the fluid considerably increases the total drilling cost. There are several approaches to avoid loss of return; one of these approaches is preventing the occurrence of the losses by identifying the lost circulation zones. Most of these approaches are difficult to apply due to some constraints in the field. The purpose of this work is to apply three artificial intelligence (AI) techniques, namely, functional networks (FN), artificial neural networks (ANN), and fuzzy logic (FL), to identify the lost circulation zones. Real-time surface drilling parameters of three wells were obtained using real-time drilling sensors. Well A was utilized for training and testing the three developed AI models, whereas Well B and Well C were utilized to validate them. High accuracy was achieved by the three AI models based on the root mean square error (RMSE), confusion matrix, and correlation coefficient (R). All the AI models identified the lost circulation zones in Well A with high accuracy where the R is more than 0.98 and RMSE is less than 0.09. ANN is the most accurate model with R=0.99 and RMSE=0.05. An ANN was able to predict the lost circulation zones in the unseen Well B and Well C with R=0.946 and RMSE=0.165 and R=0.952 and RMSE=0.155, respectively.


2021 ◽  
Author(s):  
Hector Hugo Vizcarra Marin ◽  
Alex Ngan ◽  
Roberto Pineda ◽  
Juan Carlos Gomez ◽  
Jose Antonio Becerra

Abstract Given the increased demands on the production of hydrocarbons and cost-effectiveness for the Operator's development wells, the industry is challenged to continually explore new technology and methodology to improve drilling performance and operational efficiency. In this paper, two recent case histories showcase the technology, drilling engineering, and real-time optimization that resulted in record drilling times. The wells are located on shallow water in the Gulf of Mexico, with numerous drilling challenges, which typically resulted in significant Non-Productive Time (NPT). Through close collaboration with the Operator, early planning with a clear understanding of offset wells challenges, well plan that minimize drilling in the Upper Cretaceous "Brecha" Formation were formulated. The well plan was also designed to reduce the risk of stuck pipe while meeting the requirements to penetrate the geological targets laterally to increase the area of contact in the reservoir section. This project encapsulates the successful application of the latest Push-the-Bit Rotary Steerable System (RSS) with borehole enlargement technology through a proven drilling engineering process to optimize the drilling bottomhole assembly, bit selection, drilling parameters, and real-time monitoring & optimization The records drilling times in the two case histories can be replicated and further improved. A list of lessons learned and recommendations for the future wells are discussed. These include the well trajectory planning, directional drilling BHA optimization, directional control plan, drilling parameters to optimize hole cleaning, and downhole shocks & vibrations management during drilling and underreaming operation to increase the drilling performance ultimately. Also, it includes a proposed drilling blueprint to continually push the limit of incremental drilling performance through the use of RSS with hydraulics drilling reamers through the Jurassic-age formations in shallow waters, Gulf of Mexico.


2021 ◽  
Author(s):  
Yasser Kholaif ◽  
Mahmoud Elmaghraby ◽  
Annick Nago ◽  
Jean-Michel Embry ◽  
Pramit Basu ◽  
...  

Abstract Drilling challenges in offshore Nile Delta have been largely documented in the literature. Operators are often confronted with drilling problems related to shale swelling, cavings, tight holes in combination with increased risks of lost circulation in some of the highly depleted formations. The Kafr El Sheikh shale in particular, has been linked to many instances of wellbore instability, due to its mineralogical composition (estimated to be mostly smectite, >70%). From offset well drilling experience, it could also be noticed that insufficient mud weight was often used to drill through the Kafr El Sheikh Shale, causing wellbore failure in shear due to lack of support of the wellbore wall. In the past, multiple mud weight designs have been implemented relying solely on pore pressure as lower bound of the mud window. With the increased use of geomechanics, it has been demonstrated that the lower bound should be taken as the maximum of the pore pressure and borehole collapse pressure, thus accounting for the effects of formation pressure, horizontal and vertical stresses, rock properties as well as wellbore trajectory. It has been proven that slight overpressure is often encountered halfway through the Kafr El Sheikh formation, which would typically result in slightly higher borehole collapse pressures. In the study fields, the operator expressed interest in drilling highly deviated wells (> 60-70 degrees). This raised concerns for increased drilling challenges, especially in the Kafr El Sheikh. A comprehensive and systematic risk assessment, design of a fit-for-purpose solution and its implementation during drilling took place in the fields of interest. Offset well data analytics from the subject fields supported a holistic evaluation of drilling risks associated with the Kafr El Sheikh, providing good understanding of stress sensitivity on deviation, azimuth and lithology. Upon building a robust geomechanical model, calibrated against offset well drilling experience, pre-drill mud weight and drilling practices recommendations were provided to optimize the drilling program. Near real-time geomechanical monitoring was implemented which helped to manage the model uncertainties. The implementation of a holistic risk assessment, including geomechanical recommendations and near real-time geomechanical monitoring, was effective to lead the drilling campaign successfully. As a result, three high angle wells (> 60-70 degrees) were drilled through the challenging Kafr El Sheikh formation without any hole instability. An integrated risk assessment of hole instability, managed in stages (pre-drill and during drilling), has helped to understand and simulate the behaviors of the formation. Proactive decisions have established a controlled drilling environment for successful operations.


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