A Monte Carlo approach to constraining uncertainties in modelled downhole gravity gradiometry applicationsSamuel J. Matthews 1 2 3 Craig O’Neill 1 Mark A. Lackie 1
1 Australian Research Council Centre of Excellence for Core to Crust Fluid Systems/GEMOC, Macquarie University, Sydney, NSW 2109, Australia.
2 Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC), National Farmers’ Federation House, Canberra, ACT 2600, Australia.
3 Corresponding author. Email: email@example.com
Exploration Geophysics 48(3) 305-315 https://doi.org/10.1071/EG15039
Submitted: 6 May 2015 Accepted: 11 April 2016 Published: 2 June 2016
Gravity gradiometry has a long legacy, with airborne/marine applications as well as surface applications receiving renewed recent interest. Recent instrumental advances has led to the emergence of downhole gravity gradiometry applications that have the potential for greater resolving power than borehole gravity alone. This has promise in both the petroleum and geosequestration industries; however, the effect of inherent uncertainties in the ability of downhole gravity gradiometry to resolve a subsurface signal is unknown. Here, we utilise the open source modelling package, Fatiando a Terra, to model both the gravity and gravity gradiometry responses of a subsurface body. We use a Monte Carlo approach to vary the geological structure and reference densities of the model within preset distributions. We then perform 100 000 simulations to constrain the mean response of the buried body as well as uncertainties in these results. We varied our modelled borehole to be either centred on the anomaly, adjacent to the anomaly (in the x-direction), and 2500 m distant to the anomaly (also in the x-direction). We demonstrate that gravity gradiometry is able to resolve a reservoir-scale modelled subsurface density variation up to 2500 m away, and that certain gravity gradient components (Gzz, Gxz, and Gxx) are particularly sensitive to this variation in gravity/gradiometry above the level of uncertainty in the model. The responses provided by downhole gravity gradiometry modelling clearly demonstrate a technique that can be utilised in determining a buried density contrast, which will be of particular use in the emerging industry of CO2 geosequestration. The results also provide a strong benchmark for the development of newly emerging prototype downhole gravity gradiometers.
Key words: borehole, gradiometry, gravity, Monte Carlo.
ReferencesBell, R. E., Anderson, R., and Pratson, L., 1997, Gravity gradiometry resurfaces: The Leading Edge, 16, 55–59
| Gravity gradiometry resurfaces:CrossRef |
Chilès, J.-P., and Delfiner, P., 2008, Geostatistics: modeling spatial uncertainty: Wiley Online Library.
Dodds, K., Krahenbuhl, R., Reitz, A., Li, Y., and Hovorka, S., 2013, Evaluating time-lapse borehole gravity for CO2 plume detection at SECARB Cranfield: International Journal of Greenhouse Gas Control, 18, 421–429
| Evaluating time-lapse borehole gravity for CO2 plume detection at SECARB Cranfield:CrossRef |
Dransfield, M., 2007, Airborne gravity gradiometry in the search for mineral deposits, in B. Milkereit, ed., Exploration in the New Millennium: Proceedings of the Fifth Decennial International Conference on Mineral Exploration, 341–354.
Gravitec, n.d., Gravity gradiometer. Available at: http://www.gravitec.co.nz/gravity_gradiometer.html (accessed 10 November 2015).
Hopkins, J., 1975, Gravity gradiometry - a rebirth: Canadian Journal of Exploration Geophysics, 11, 34–37
Jacob, T., Rohmer, J., and Manceau, J.-C., 2016, Using surface and borehole time-lapse gravity to monitor CO2 in saline aquifers: a numerical feasibility study: Greenhouse Gases: Science and Technology, 6, 34–54
| Using surface and borehole time-lapse gravity to monitor CO2 in saline aquifers: a numerical feasibility study:CrossRef |
Jekeli, C., 1993, A review of gravity gradiometer survey system data analyses: Geophysics, 58, 508–514
| A review of gravity gradiometer survey system data analyses:CrossRef |
Kearey, P., Brooks, M., and Hill, I., 2002, An introduction to geophysical exploration (3rd edition): Blackwell Publishing.
Lockerbie, N., 2013, Development of a downhole gravity gradiometer (AMADEUS). University of Strathclyde Glasgow. Available at https://pure.strath.ac.uk/portal/en/projects/development-of-a-downhole-gravity-gradiometer-amadeus(4c3b214b-d607-4b03-9e6a-c6c04e69643d).html
Nagy, D., Papp, G., and Benedek, J., 2000, The gravitational potential and its derivatives for the prism: Journal of Geodesy, 74, 552–560
| The gravitational potential and its derivatives for the prism:CrossRef |
pbEncom, 2014, ModelVision v14.0 User Guide, pp. 675–678. Available at: http://www.pitneybowes.com/content/dam/pitneybowes/pbencom/en/modelvision/M odelVision14_User_Guide.pdf (accessed 12 October 2015).
Uieda, L., Oliveira, V. C., Jr, and Barbosa, V. C. F., 2013, Modeling the Earth with Fatiando a Terra: Proceedings of the 12th Python in Science Conference (SciPy 2013), 96–103.