Oswaldo Davogustto

Anomalous cold in the Pangaean tropics

The late Paleozoic archives the greatest glaciation of the Phanerozoic. Whereas high-latitude Gondwanan strata preserve widespread evidence for continental ice, the Permo-Carboniferous tropics have long been considered analogous to today9s: warm and shielded from the high-latitude cold. Here, we report on glacial and periglacial indicators that record episodes of freezing continental temperatures in western equatorial Pangaea. An exhumed glacial valley and associated deposits record direct evidence for glaciation that extended to low paleoelevations in the ancestral Rocky Mountains. Furthermore, the Permo-Carboniferous archives the only known occurrence of widespread tropical loess in Earth9s history; the volume, chemistry, and provenance of this loess(ite) is most consistent with glacial derivation. Together with emerging indicators for cold elsewhere in low-latitude Pangaea, these results suggest that tropical climate was not buffered from the high latitudes and may record glacial-interglacial climate shifts of very large magnitude. Coupled climate–ice sheet model simulations demonstrate that low atmospheric CO 2 and solar luminosity alone cannot account for such cold, and that other factors must be considered in attempting to explain this “best-known” analogue to our present Earth.

Detecting stratigraphic discontinuities using time-frequency seismic phase residues

Spectral decomposition is a proven, powerful means of identifying strong amplitude anomalies at specific frequencies that are otherwise buried in the broadband response. Most publications focus on using spectral magnitude instead of phase components to identify lateral changes in stratigraphy, wavefield attenuation from the quality factor Q, and unconformities between geologic formations. Although seismic acquisition and processing preserve phase very well, little has been published about interpreting the phase components resulting from spectral decomposition. Morlet complex wavelet transform phase residues can improve seismic spectral decomposition interpretation by detecting the phase discontinuities in the joint time-frequency spectral phase component. Phase singularities can be associated with geologic features, and work with phase residues can improve interpretation of the Anadarko basin Red Fork channels of Oklahoma, U.S.A.

Resolving subtle stratigraphic features using spectral ridges and phase residues

AbstractSeismic interpretation is dependent on the quality and resolution of seismic data. Unfortunately, seismic amplitude data are often insufficient for detailed sequence stratigraphy interpretation. We reviewed a method to derive high-resolution seismic attributes based upon complex continuous wavelet transform pseudodeconvolution (PD) and phase-residue techniques. The PD method is based upon an assumption of a blocky earth model that allowed us to increase the frequency content of seismic data that, for our data, better matched the well log control. The phase-residue technique allowed us to extract information not only from thin layers but also from interference patterns such as unconformities from the seismic amplitude data. Using data from a West Texas carbonate environment, we found out how PD can be used not only to improve the seismic well ties but also to provide sharper sequence terminations. Using data from an Anadarko Basin clastic environment, we discovered how phase residues delineate inci...

Anomalous cold in the pangaean tropics: Reply

We thank W. [Hood et al. (2009)][1] for their Comment on our Geology paper ([Soreghan et al., 2008][2]). We recognize that our hypothesis of episodic cold in the Pangaean tropics, which relies, in part, on our proposal of a late Paleozoic age and glacial origin for Unaweep Canyon, is radical. Hence

P- and S-wave delineation of the Horseshoe Atoll, Diamond-M Field, Texas, USA

This paper presents an applied workflow for displaying seismic multi-attributes and integrating the results into the interpretation of a carbonate reservoir. This analysis compares the processed volume of the conventional P-wave data (PP) with the S-wave data (SH-SH) over the same extended area to improve understanding of the morphology of the reef “build-up” structure within the Canyon Reef Formation. The final goal is to identify bypassed compartments in the reservoir.

Integrating phase into the visualization of spectral decomposition attributes

AbstractMuch of the world’s conventional oil and gas production comes from fluvial-deltaic reservoirs. The ability to accurately interpret the architectural elements comprising these systems greatly reduces the risk in exploration and development in these environments. We have evaluated methods for using spectral decomposition attributes to improve the visualization in fluvial-deltaic environments using data from the Middle Pennsylvanian age Red Fork Formation of Oklahoma. We determined how spectral phase and magnitude attributes can be effectively combined using an hue-saturation-value color map to produce images that have considerable interpretational value. Incorporating our methods in the interpretation process has the potential to improve the exploration and development in these systems.

Using Diffusion Maps for Latent Space Analysis on Seismic Waveforms of Incised Valleys in the Anadarko Basin, Oklahoma, USA

In this work we present a new method for latent space mapping based upon inter-point similarities. This method, diffusion maps, has a number of nice qualities compared with previous methods including the fact that it is based upon inter-point similarities rather than a Euclidean space. We then demonstrate application of this approach to mapping an incised valley system from the Anadarko Basin, Oklahoma, USA. Multi-dimensional data is commonly encountered in attribute analysis where the desire is to combine several attributes with complementary properties. As geophysicists, we tend to view attribute spaces higher than four dimensional as being undesirable as they cannot be visualized using common color models such as ARGB space. Furthermore, mathematical considerations such as the Curse of Dimensionality (Bellmann, 1957) make working in lower dimensional space necessary. (Guo, Marfurt, Liu, & Dou, 2006) discussed an unsupervised learning method for doing dimensionality reduction of attributes using Principal Component Analysis (PCA). While this method has been shown to be useful in a broad range of applications, they are limited in their ability to capture non-linear structure in multidimensional attribute space. Retaining this non-linearity is important as data sets generally present a heterogeneous mix of latent processes that, taken as a whole, are unlikely to be well represented by a single lowdimensional linear manifold. A number of non-linear methods of manifold learning have been applied to seismic attributes and waveform modeling (Wallet & Marfurt, 2008) . Self organizing maps (SOM) is the best known of these approaches, and it is available in a number of commercial products. (Wallet & Perez, 2009) also demonstrated the use of a statistical method, generative topographical maps (GTM). (Wallet & Perez, 2009) applied diffusion maps to the problem of modeling well log data. They noted that the high computational demands of diffusion maps was an impediment to scaling to reasonable sized seismic problems. In this paper, we present an estimation method that deals with this problem.

Delineation By Seismic Attributes of Fracture Patterns In a 3D GPR Data Volume

Summary Fractures are caused by changes in stress patterns. The main objective of this study is to delineate and map fractures in a granitic body with the help of attribute algorithms. The data is a 3D GPR survey consisting of 24 parallel lines. Changes in the dielectric constant between the granite and the fracture fill (air or water) will produce a distinctive amplitude fracture response. Amplitude attribute algorithms allow the identification of fracture patterns. The resulting fracture interpretation is corroborated by the surface fracture data.

Footprint Removal Using Adaptive Subtraction Algorithms For Seismic Attribute Quality Enhancement: A Case Study of Anadarko Basin Red Fork Incised Valley System.

Acquisition footprint often poses a major problem in land 3D seismic data. Some of the causes for footprint are constraints on survey design, backscattered noise, lateral variations of fold, offset, and azimuth distributions, and spatial aliasing. Faced with extracting subtle features contained in seismic amplitudes, interpreter is often confronted with footprint that can mask important details critical to the identification of key reservoir properties. In this paper, we show the results of footprint suppression using adaptive subtraction to enhance the data quality of a survey acquired over a Red Fork incised valley complex without removing “geological features” of interest.