Title page for ETD etd-12152003-154103


Type of Document Master's Thesis
Author Solano, Jaime
Author's Email Address jsolan1@lsu.edu
URN etd-12152003-154103
Title Evaluation of New Methods for Processing Drilling Data to Determine the Cause of Changes in Bit Performance
Degree Master of Science in Petroleum Engineering (M.S.P.E.)
Department Petroleum Engineering
Advisory Committee
Advisor Name Title
John R. Smith Committee Chair
Andrew Wojtanowicz Committee Member
Christopher White Committee Member
Yilmaz Karasulu Committee Member
Keywords
  • balling
Date of Defense 2003-12-05
Availability unrestricted
Abstract
Drilling operations represent the major cost in finding and developing new petroleum reserves. Poor drilling performance when drilling deep shale and strong rocks, as evidenced by slow rate of penetration (ROP), has a significant detrimental impact on drilling costs. Also, it has been concluded that bit balling is the main cause of low ROP when drilling deep, clay-rich shale with water-based mud. In addition, it is estimated that a potential saving in drilling cost of hundreds of millions of dollars a year can be obtained if bit balling is mitigated and ROP is improved.

Several methods have been developed in order to improve bit performance. Recently, Arash Aghassi 1 and John R. Smith 37 proposed one of them, which uses simple drilling data to identify bit balling and lithology change as two separate effects through the calculation of five diagnostic parameters and comparing these values to a “baseline” zone. The objective of this research is to apply, evaluate, and improve the method proposed by Aghassi and Smith.

A set of down-hole well data and several sets of surface well data were used to evaluate the method. The diagnostic parameters of Aghassi’s method were calculated, first using the down-hole data, and then with surface data. All of the results were correlated with and compared to wire-line logs. As a result, the utility of using surface data was confirmed. The overall utility of the method and its diagnostic parameters for detecting the occurrence of, and increases in, the severity of bit balling as distinguished from drilling into a stronger rock were evaluated. The results were very sensitive to the selection of the baseline; also, when drilling strong rock, the interpretation of the diagnostic parameters is sometimes that the bit is balled.

Statistical “Logistic Regression” models were developed and evaluated as a means to solve these problems. Those models were applied using several sets of well data. As a result, it was determined that the logistic regression can potentially provide a basis for distinguish between bit balling and strong rock. It can be used independently, but it is more effective as a complement to Aghassi & Smith’s method.

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