Engineering Commons^™

Field Drilling Data Cleaning And Preparation For Data Analytics Applications, Daniel Cardoso Braga

LSU Master's Theses

Throughout the history of oil well drilling, service providers have been continuously striving to improve performance and reduce total drilling costs to operating companies. Despite constant improvement in tools, products, and processes, data science has not played a large part in oil well drilling. With the implementation of data science in the energy sector, companies have come to see significant value in efficiently processing the massive amounts of data produced by the multitude of internet of thing (IOT) sensors at the rig. The scope of this project is to combine academia and industry experience to analyze data from 13 different …

Influence Of Frictional Or Rotational Kinetic Energy On Wellbore-Fluid/Temperature Profiles During Drilling Operations, Ahmed Q. Al Saedi, Ralph E. Flori, C. Shah Kabir

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Temperature-profile distributions in a wellbore during drilling operations might take different forms when applying the energy balance in the overall system. For steady-state conditions, wherein the wellbore is considered a closed system, adding any source of additional energy to this system can influence the predicted temperature profiles. This study presents a new analytical model to investigate the influence of rotational energy arising from the drillstring operation on the wellbore-temperature behavior.

A significant part of the drilling operation is rotation of the drillstring. Depending on the drilling rig, various equipment provides this kind of energy, such as the rotary table or …

Drilling Performance Monitoring And Optimization: A Data-Driven Approach, Mehdi Khazaeli, S. Lashari, A. Takbiri-Borujeni, E. Fathi, T. Sun

All Faculty Articles - School of Engineering and Computer Science

Drilling performance monitoring and optimization are crucial in increasing the overall NPV of an oil and gas project. Even after rigorous planning, drilling phase of any project can be hindered by unanticipated problems, such as bit balling. The objective of this paper is to implement artificial intelligence technique to develop a smart model for more accurate and robust real-time drilling performance monitoring and optimization. For this purpose, the back propagation, feed forward neural network model was developed to predict rate of penetration (ROP) using different input parameters such as weight on bit, rotations per minute, mud flow (GPM) and differential …

Horizontal Flow Loop Design For The Study Of Drill String Rotation Effects On Cuttings Transport, David C. Rathgeber

Graduate Theses & Non-Theses

Exploration and Production companies are continually focusing more time, energy and resources into Extended Reach Drilling in order to maximize reservoir production while minimizing both environmental impact and development costs. These long laterals (2:1 Measured Depth: True Vertical Depth) are often more difficult to drill and can be severely impacted by inadequate drilling practices. Cuttings transport efficiency is a critical parameter of Extended Reach Drilling operations, and poor wellbore cleaning can lead to excessive torque, drag, and several other serious downhole problems.

Although many studies have been performed that identify the importance of drill string rotation on cuttings movement, there …

String Out And Compressibility Effect On Pressure Rise In A Shut-In Well, Nicholas Henry

LSU Master's Theses

Gas kick migration experiments were performed in a small-scale well prototype model of annular geometry to analyze the behavior of gas kicks in highly non-Newtonian fluids. The objective was to isolate and estimate the effects system compressibility and bubble string out have on the pressure build up in a situation in which a gas kick rises through a noncirculating drilling mud in a vertical well.

The experiments consisted of 2 tests. The first test measured the apparent compressibility of the liquid phase of the experiment – that phase which simulated the drilling mud in a gas kick situation. The second …

Drilling Performance Monitoring And Optimization: A Data-Driven Approach, Shan E Zehra Lashari, Ali Takbiri-Borujeni, Ebrahim Fathi, Ting Sun, Reza Rahmani, Mehdi Khazaeli

Faculty & Staff Scholarship

Abstract Drilling performance monitoring and optimization are crucial in increasing the overall NPV of an oil and gas project. Even after rigorous planning, drilling phase of any project can be hindered by unanticipated problems, such as bit balling. The objective of this paper is to implement artifcial intelligence technique to develop a smart model for more accurate and robust real-time drilling performance monitoring and optimization. For this purpose, the back propagation, feed forward neural network model was developed to predict rate of penetration (ROP) using diferent input parameters such as weight on bit, rotations per minute, mud fow (GPM) and …