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With the increasing size of the seismic data volumes, machine learning applications have been found to accelerate the discrimination of seismic facies used in the identification of geologic patterns, defining stratigraphy and the direct indication of hydrocarbons. Many practitioners have demonstrated the application of dimensionality reduction tools such as principal component analysis and independent component analysis, or clustering techniques. Some of these are available in several commercial interpretation software packages.

Show more American Association of Petroleum Geologists (AAPG)
Desktop /Portals/0/PackFlashItemImages/WebReady/choices-of-attributes-for-unsupervised-hero.jpg?width=100&h=100&mode=crop&anchor=middlecenter&quality=75amp;encoder=freeimage&progressive=true Choice of Attributes for Unsupervised Seismic Facies Classification

In the world of oil and gas, an increasing number of plays in stratigraphic traps are being made – in large part due to ever-evolving seismic technology. The Discovery Thinking forum at the annual IMAGE conference in August served to highlight some of these plays in offshore frontier basins and the role that geophysics played in their discovery. “We are seeing more giant stratigraphic fields, and seismic is the key,” said past AAPG President Charles A. Sternbach, chair of the Discovery Thinking forum. “And, we are seeing more oil found at greater depths. Unconventional plays are migrating outside of the Western Hemisphere.”

Show more American Association of Petroleum Geologists (AAPG)
Desktop /Portals/0/PackFlashItemImages/WebReady/geophysics-has-proven-key-hero.jpg?width=100&h=100&mode=crop&anchor=middlecenter&quality=75amp;encoder=freeimage&progressive=true Geophysics Has Proven Key in Giant Stratigraphic Fields Discoveries

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