The future of seismic data acquisition clearly dictates increased sampling in both receiver and shot domains. A significant amount, almost 80%, of the total cost of an exploration and development seismic project is spent on data acquisition. It is, therefore, extremely important that we reduce acquisition-related costs and at the same time we strive to improve seismic data quality. Indeed, the number of seismic channels follows a form of Moore's law; that is, the number of channels laid out in the field is steadily increasing by an order of magnitude every 10 years (Figure 1) while the recent introduction of simultaneous sources provides improved spatial sampling in the shot domain. Figure 2 shows three time slices that clearly demonstrate the link between increased number of channels recorded and improved resolution and image quality.

Automation in geophysical data acquisition: From ocean-bottom nodes to RoboNodes

In autonomous underwater vehicles (AUVs) the onboard power used to complete missions is limited. To solve this problem, a landing AUV has been designed, which conserves energy by sitting on the seafloor while monitoring the ocean. In order to study the dynamic behaviors for better control of the AUV, the dynamic analysis of the landing AUV is presented in this paper. Based on the momentum theorem and the angular momentum theorem, the dynamic model of the landing AUV is derived. The simulations of rectilinear motion, rotary motion and helix motion indicate the dynamic behaviors of the AUV. The ocean experiments validate the dynamic model presented in this paper. The experiments also verify that the landing AUV can work for a longer time than common AUVs.

Dynamic Analysis of Landing Autonomous Underwater Vehicle

Advances in robotics have led to the development of autonomous platforms
capable of exploring regions that are inaccessible for humans These
regions range from extra-terrestrial surfaces, such as Mars and Titan, to the
bottom of our oceans In addition to robotics there have also been advances
in sensor technologies in areas such as power consumption, size, weight, and
communications The combination of field robotics with novel sensing capabilities
provides exciting science opportunities Autonomous measurement
of phenomena present in the environment offers an alternative to expensive,
time-consuming manual measurements
This thesis investigates the novel use of a miniaturised X-Ray Fluorescence
(XRF) spectrometer sensor system as part of the scientific payload on
an Autonomous Underwater Vehicle (AUV) This will allow the automated
in situ semi-quantitative analysis of heavy metal contamination present in
marine sediments Heavy metal contamination of sediments is particularly
important because of its potential impact on associated ecosystems and human
health
To achieve this capability the XRF system has been integrated with the
AUV using a custom housing that enables the sensor to be operated safely
underwater A landing behaviour has been developed for the AUV that enables
the vehicle to land on the seabed, without signicantly disturbing the
sediment layer, and to then remain in a stationary position for the duration
of the measurement Automated data analysis using genetic algorithms
was performed on the XRF data on-board the vehicle This would enable
the AUV control system to make informed decisions based on the results of
measurements facilitating adaptive sampling strategies
A total of 21 in situ measurements have been performed in the Derwent
estuary region, located in south-east Tasmania, Australia The results show
significantly higher relative heavy metal concentrations in areas of industrial
activity This demonstrates the developed system can perform in situ measurements that can be used to observe spatial variations in heavy metal
contamination The resulting data from these measurements can guide further
comprehensive environmental monitoring missions by supporting site
selection or assisting with the remediation of contaminated sediments
The research contribution presented in this thesis has been the development
of the capability to autonomously and intelligently perform in situ
measurements and data analysis of marine sediments using an AUV equipped
with a miniaturised XRF spectrometer The next stage of this research will
aim to increase the scientific return of measurement missions by the realtime
inclusion of scientific sensor data in decision-making processes to enable
adaptive sampling

Chemical analysis of sediments using X-Rayfluorescence on-board an AutonomousUnderwater Vehicle

Autonomous underwater vehicles (AUVs) have become main tools for underwater survey in scientific, military, and commercial applications. A significant amount of onboard power is needed to execute long-range missions; however, energy storage is limited in AUV. This paper presents a novel landing AUV that can land on the sea floor to perform long-term monitoring and measuring tasks and save onboard electric energy. The AUV has following characteristics. Firstly, a triangular structure of the AUV which is composed of three cabins is used to achieve stable bottom sitting. Secondly, the releasing mechanism is designed to eject and recover the AUV. Bottom sitting and recovering is verified by ocean trials. This paper provides guidance for design of similar AUVs.

Fei Liu

Papers

Design and optimization of overall structure for a landing AUV