BUSA 421 Data Mining

Business Case 2
BUSA 421 Data Mining
Spring 2021
Instructor: Prof. Brodnax
Academic Integrity: DO NOT share your work with other students!
INCOME _ DISTRICT _ CON
EDITION
B&R Oil and Gas records a variety of drilling performance measures. To investigate the importance of the slant drilling technique, the Cotton Valley data posted in the assignment course content area shows the field drilled, slant rate differential, core fracture ratio (including injection points), and percentage of successful production drilling (Successful % Production Completion – Online) for a random sample of 18 wells drilled in the Cotton Valley Zone as part of the 2013 drilling projects (Cotton Valley Data Workbook is posted for this business case).
Requirements:
a. Develop the estimated regression equation that could be used to predict the percentage of successful drilling completions, given the slant differential. 1. What is the regression equation? Explain it. 2. What is R-square and what does it tell you? 3. What does the P value of the slant rate differential tell us? 4. Explain what proportion of the variable in the sample values to the proportion of successful drilling projects does this model explain? 5. What is the implication of this regression model to management (the big question)? Provide objective evidence graphs as appropriate.
b. Develop the estimated regression equation that could be used to predict the percentage of successful drilling completions, given the core fracture ratio. 1. What is the regression equation? Explain it. 2. What is R-square and what does it tell you? 3. What does the P value of the core fracture ratio tell us? 4. Explain what proportion of the variable in the sample values to the proportion of successful drilling projects does this model explain? 5. What is the implication of this regression model to management (the big question)? Provide objective evidence graphs as appropriate.
c. Develop the estimated multiple regression equation that could be used to predict the percentage of successful drilling completions, given the slant differential and the core fracture ratio. 1. What is the regression equation? Explain it. 2. What is R-square and what does it tell you? 3. What does the P value of the model tell us? 4. Explain what proportion of the variable in the sample values to the proportion of successful drilling projects does this model explain? 5. What is the implication of this regression model to management (the big question)? Provide objective evidence graphs as appropriate. 6. e. Provide the residual plots in this document.
d. The slant differential for another well in the Cotton Valley Zone drilled during 2013 was 5.3, with a core fracture ratio of 0.053. Use the estimated regression equation developed in part c to predict a successful drilling completion during that year. Explain what the result means.
e. Based on the regression models run, what insight / recommendation would you provide to management? Explain in detail. (Major: A data mining focus item to tie it all together for management as discussed.)
Follow the examples as provided in the discussion/lecture videos, material documents, and especially the associated analyst guides. These should provide similar approaches to the requirements noted in this business case. Additionally, analyst guides will be provided to support the specific requirements for this business case. Please save your answers into a Word document clearly identifying which question and sub-question you are responding to. As this is a business case, be sure and provide appropriate detail in this document as it is the primary document that will be reviewed by management. Also, you must post the excel workbook as part of the objective evidence as to how you derived your responses. Detail responses to what the information means from a management perspective is required to get full credit, not just what the tool provides from the data. You must post both documents in the “Business Case 2 Dropbox” NLT 11:59 PM on 14 March.

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