Using Data Mining to Stop or Mitigate Lost Circulation


Lost circulation materials (LCMs) are available in a great variety of materials, sizes, and can vary in the method of application. Selecting the right LCM and treatment for the job is critical in achieving the successful control of the lost circulation event.

After reading a good number of papers and case histories regarding lost circulation materials and treatments and comparing the current classification to actual real field data, a large gap was found in the current calcification of lost circulation materials and treatments. An updated classification of lost circulation materials and treatments was provided based on the type of losses and applications.

Data were collected on both LCM and applications from various number of sources in the Basra area of Iraq where drilling operations are highly susceptible to lost circulation in the Dammam, Hartha and Shuaiba formations. After analyzing the data, the best lost circulation treatments and materials to treat seepage, partial, severe, and complete losses in Basra oil fields were provided as a flowchart accomplished by practical guidelines that can serve as a reference material for the drilling personnel when responding to lost circulation in the field.

This paper will also discuss methods that are used to ameliorate lost circulation without the use of traditional lost circulation materials. Example of the alternative approaches include discussions of blind drilling and floating mud cap drilling using case histories from the Basra fields.

The results of this analysis provide a path forward for effectively and systematically using lost circulation materials and treatments in the Basra area. The methodologies presented in this work can be adapted and used to treat lost circulation worldwide.


Geosciences and Geological and Petroleum Engineering

Keywords and Phrases

Drilling fluid; Lost circulation; Updated classification; Basra oil fields; Iraq

Geographic Coverage


International Standard Serial Number (ISSN)

0920-4105; 1873-4715

Document Type

Article - Journal

Document Version


File Type





© 2019 Elsevier, All rights reserved.

Publication Date

01 Feb 2019


Article Location