Acoustic impedance to outcrop: Presenting near-surface seismic data as a virtual outcrop in carbonate analog studies

Ahmad Ramdani*, Andika Perbawa, Ingrid Puspita, Volker Vahrenkamp

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Outcrop analogs play a central role in understanding subseismic interwell depositional facies heterogeneity of carbonate reservoirs. Outcrop geologists rarely utilize near-surface seismic data due to the limited vertical resolution and difficulty visualizing seismic signals as "band-limited rocks."This study proposes a methodology using a combination of forward modeling and conditional generative adversarial network (cGAN) to translate seismic-derived acoustic impedance (AI) into a pseudo-high-resolution virtual outcrop. We tested the methodology on the Hanifa reservoir analog outcropping in Wadi Birk, Saudi Arabia. We interpret a 4 km long outcrop photomosaic from a digital outcrop model (DOM) for its depositional facies, populate the DOM with AI properties, and forward calculate the band-limited AI of the DOM facies using colored inversion. We pair the synthetic band-limited AI with DOM facies and train them using a cGAN. Similarly, we pair the DOM facies with outcrop photos and train them using a cGAN. We chain the two trained networks and apply them to the approximately 600 m long seismic-derived AI data acquired just behind the outcrop. The result translates AI images into a virtual outcrop "behind-the-outcrop"model. This virtual outcrop model is a visual medium that operates at a resolution and format more familiar to outcrop geologists. This model resolves subseismic stratigraphic features such as the intricate downlap-onlap stratal termination at scales of tens of centimeters and the outline of buildup facies, which are otherwise unresolvable in the band-limited AI.

Original languageEnglish (US)
Pages (from-to)599-610
Number of pages12
JournalLeading Edge
Issue number9
StatePublished - Sep 1 2022


  • Acoustic
  • Artificial intelligence
  • Carbonate
  • Geology
  • Middle East

ASJC Scopus subject areas

  • Geophysics
  • Geology


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