Building an intelligent system for the prediction of subsurface lithology and other petrophysical variables using ODP downhole log combinations and artificial neural networks

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doi: 10.1306/A9675020-1738-11D7-8645000102C1865D
Author(s): Teliatnikov, Ivan; Müller, Dietmar R.
Author Affiliation(s): Primary:
University of Sydney, Sydney, N.S.W., United States
Volume Title: AAPG international conference and exhibition; abstracts
Source: AAPG Bulletin, 84(9), p.1504; AAPG international conference and exhibition, Bali, Indonesia, Oct. 15 - 18, 2000. Publisher: American Association of Petroleum Geologists, Tulsa, OK, United States. ISSN: 0149-1423 CODEN: AABUD2
Note: In English
Summary: A large proportion of the data available for marine geologists and geophysicists during the last 25 years originated from the Deep-Sea Drilling Project (DSDP) and its successor since 1984, the Oceanic Drilling Program (ODP). Under these programs more then 1000 holes were drilled, cored and logged in nearly all geological environments of the wold's oceans. The databases of cores, corresponding downhole geophysical measurements and seismic reflection data have been developed and become readily available for the scientific community. In our work we utilise parts of these data in an attempt to develop a robust and general classification scheme based on Artificial Neural Networks. The scheme is capable of extracting lithostratigraphic information and petrophysical parameters from the well data from an arbitrary location and without need for further training. A potentially new method of automated quality control for selection of representative data points used for training of the classification scheme is discussed. This method is based on the analysis of high resolution Formation Microscanner Images. Finally we present a case-study where we used the discussed methodology to develop a classification of volcanic sequences allowing us to identify relationship between volcanic lithosediments and their seismic and log signatures.
Year of Publication: 2000
Research Program: DSDP Deep Sea Drilling Project
ODP Ocean Drilling Program
Key Words: 20 Geophysics, Applied; 29 Economic Geology, Energy Sources; Artificial intelligence; Cores; Data bases; Data processing; Deep Sea Drilling Project; Geophysical methods; Information management; Marine sediments; Neural networks; Ocean Drilling Program; Petroleum; Petroleum exploration; Sediments; Seismic methods; Well-logging
Record ID: 2000072529
Copyright Information: GeoRef, Copyright 2019 American Geosciences Institute. Reference includes data supplied by American Association of Petroleum Geologists, Tulsa, OK, United States

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