Revealing the subsurface - Creation of real-time gravity maps for engineering targets

In 1500 Leonardo Da Vinci stated that we know more about the stars above us than the ground beneath our feet. That is as true today as it was then.  In particular we don’t know where our shallow buried assets (first 2 metres below the ground surface) are located, yet a complete picture is essential for civil engineering and construction projects to reduce the risk from buried assets. Despite existing current methods to enhance this knowledge, there is a reported annual cost of over £200 million per year in the United Kingdom from utility strikes, highlighting the requirement for improvement in this sector. One sensing technology which could address some of the limitations with existing sensors is gravity. However, one challenge with existing gravity measurements is associated with the time-consuming and complex post-processing required to convert the measured data into meaningful gravity information in order to produce initially 2D gravity maps. This currently prohibits real-time data processing producing gravity maps on site as well as limits survey optimisation as there is no direct feedback loop between the survey methodology and any buried features. Therefore, gravity surveys are time consuming and costly. 

This exciting and interdisciplinary project offers collaboration with the funders in an interactive and multi-disciplinary team comprising engineers and physicists. It has access to a state-of-the-art large-scale testing laboratory (National Buried Infrastructure Facility).The research will significantly modify the current work flow of collecting gravity data and the time it takes to process by developing advanced quality control procedures. This will transform the operational capability of gravity surveying through efficient data rejection and enabling novel gravity survey methodologies which can be dynamically targeted, facilitating drastic reductions in information feedback to users. While this is of significant commercial interest, it is also critical for enabling gravity surveys in the defence sector where access to sites is often hazardous and time limited. Realising these advances will relax operational constraints allowing defence end users to investigate applications such as the detection of hidden voids and caches, tunnels, and bunkers.

Applicants should have a good primary degree (First- or Second-class Honours) or MSc in an engineering, physics, geophysics or mathematics discipline with good data processing and numerical modelling skills. The successful candidate should be highly motivated, have good communication skills and must be prepared to work within a multidisciplinary team and with other PhD students. Some experience working in the field or the laboratory would be advantageous. A successful candidate will be required to have a driving licence to facilitate the field collection of data.