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Interstate Technical Group on Abandoned Underground Mines
An Interactive Forum

Quality Control in Geophysics Abstract

Presenter: Dr. Gary Olhoeft, Professor of Geophysics
University/Organization: Colorado School of Mines
Phone: 303-273-3458
Fax: 303-273-3478
Email: golhoeft@mines.edu
Mailing Address: 1500 Illinois Street
Golden, Colorado 80401-1887


When someone is given an answer to a problem, they almost always want to know, how well is that answer known? Quality control is the process that defines how well the solution is known for a problem. It is preferably given quantitatively, but with real world constraints, that may be only partly possible. The quality control process begins with the definition of the problem to be solved. It then assesses impact on quality from all steps along the way to the solution, and it includes a description of the criteria for a successful solution. These steps include selecting the appropriate tools and procedures to acquire data, determine and describe constraints, document procedures, process data, model data, interpret results, and present the results to the people with the problem, along with an assessment of how well the problem was solved. Quality control includes a variety of subprocesses along the overall path to solution. Some of these include analyses of data measurement error, noise, interference, processing biases, model assumptions, interpreter prejudices, and much more. These require development of procedures and methods to test data, determine errors, recognize and identify sources of noise and interferences, check for and resolve inconsistencies between datasets, test processing, and so forth. Quality control also includes consequences of constraints such as site access limitations, risk, hazards and safety requirements, conflicts and compromises, available resources (including people, equipment, and funding), and other issues (regulatory, litigation, proprietary, security, liability, insurance, training, licenses, customs, etc.). Quality control becomes most important for problems where the answer may be a negative - as in proving the absence of something like a void. Quality control can help answer questions like what is the biggest void that might be there that couldn't be detected by the process performed? These types of questions are often important in hazard and risk analysis, for example in advance of mining. Quality control goes beyond any single discipline, but is discussed here only in the context of geophysics.

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Updated: 06/27/2017
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