Abstract There has been debate over the processes acting on deep-water channels, with comparisons made to the evolution of meandering fluvial systems. We characterized a three-dimensional seismic-reflection dataset of the Joshua deep-water channel–levee system located in the eastern Gulf of Mexico and interpreted 13 horizons showing its kinematic evolution over a 25 km reach. Over this reach, we documented channel migration through systematic bend expansion and downstream translation, which was sustained through channel aggradation as sinuosity increased from 1.25 to 2.3 at abandonment. An abrupt decrease in sinuosity was associated with a neck cutoff, which changed the subsequent migration direction of the channel in that locality. These processes are analogous to the evolution of meandering fluvial systems. We show that increasing channel sinuosity correlates to a reduction in channel slope and hypothesize that this promoted increasingly depositional turbidity currents that led to channel aggradation. Using a simple forward stratigraphic model in which vertical movements of the channel are governed by a stream power law, we show how aggradation can be driven autogenically. Trends in sinuosity, aggradation and slope are in broad agreement between the Joshua Channel and the model. This highlights the potential importance of intrinsic channel processes as a control on system evolution.

Our seismic data are a kind of digital palimpsest: a manuscript written on imperfectly erased reused paper that contains multiple overlapping layers of writing. Each layer of writing has its own story; it may be fresh and distinct, easy to read, or broken up into fragments and faded into near invisibility. In our processing we typically pay the most attention to the data layer that we plan to use for imaging, and ignore the others to the extent that we can get away with doing so. The deeper layers become “noise”. However, the better we can understand the various layers of the data, the better we can turn each layer into either additional useful signal or structured (i.e. predictable) noise. Preserving the structure of the noise is important. It allows us to do better, possibly much better, than we could by treating it as Gaussian random noise. For random noise the best we can typically do is stacking. While stacking is a powerful tool, its noise-suppression abilities are effective only up to a point. Each incremental increase in the stack size N costs the same to acquire, yet results in ever less S/N improvement. Even worse, noise in real data often contains statistical outliers that will dominate over the noise-suppression power of stack as N becomes large. We can damage our data at every step of the process from acquisition to final delivered product. If you are not checking for problems, you may be unaware that anything is amiss. The next game-changing improvement in our ability to guide business decisions by producing higher-quality Earth images may only happen if we can treat our seismic data with greater scientific rigor than has been standard practice. The goal of this book is to teach you the skills that you will need to do that.

Abstract The Oligocene–Miocene Catahoula Formation occurs along the length of the Gulf of Mexico coastal plain from the Rio Grande to the state of Mississippi. In Starr County, in South Texas, the formation is typified by the 20 m-thick Catahoula Volcanic Ash, interpreted to represent a single caldera eruption. The massive ash fall is the main source of the uranium that has been mined in South Texas since the late 1950s. It is also the origin of massive amounts of petrified wood, which was used in prehistory for making projectile points and continues to be used for landscaping. Diagenetic alteration of the volcanic ash produced the distinctive El Sauz Chert, which was used by native Americans for 10 000 years to make projectile points. More recently, the Catahoula Volcanic Ash was used as pozzolanic aggregate with Portland cement for the construction of Falcon Dam. The outcrop of the Catahoula Volcanic Ash in Starr County is the centrepiece of a geoheritage initiative, titled ‘ Ancient Landscapes of South Texas at the Nexus of Natural and Cultural History ’, whose goal is to connect the earth and social sciences to educate residents, students and visitors in how the region's geology has played a significant role in its social history.