Outputs (10)

Going round in circles: Geometry in the early years (2023)
Journal Article
Oughton, R. H., Wheadon, D. M., Bolden, D. S., Nichols, K., Fearn, S., Darwin, S., Dixon-Jones, S., Mistry, M., Peyerimhoff, N., & Townsend, A. (2023). Going round in circles: Geometry in the early years. Mathematics teaching, 286, 29-34

The research described here came from a collaboration between university-based mathematicians and early years (EY) educators. The project emerged naturally, driven by the felt need of the EY educators to develop a broader understanding and appreciati... Read More about Going round in circles: Geometry in the early years.

Developing ‘deep mathematical thinking’ in geometry with 3- and 4-year-olds: A collaborative study between early years teachers and University-based mathematicians (2022)
Journal Article
Oughton, R., Nichols, K., Bolden, D. S., Dixon-Jones, S., Fearn, S., Darwin, S., Mistry, M., Peyerimhoff, N., & Townsend, A. (2024). Developing ‘deep mathematical thinking’ in geometry with 3- and 4-year-olds: A collaborative study between early years teachers and University-based mathematicians. Mathematical Thinking and Learning, 26(3), 306-325. https://doi.org/10.1080/10986065.2022.2119497

Mathematics in early years settings is often restricted to learning to count and identifying simple shapes. This is partly due to the narrow scope of many early years curricula and insufficient teacher training for exploring deeper mathematical conce... Read More about Developing ‘deep mathematical thinking’ in geometry with 3- and 4-year-olds: A collaborative study between early years teachers and University-based mathematicians.

The effects of nutrition and health claims on the nutrient composition of single and subsequent meal servings (2022)
Journal Article
Benson, T., Bucher, T., Oughton, R., McCloat, A., Mooney, E., Farrell, S., & Dean, M. (2022). The effects of nutrition and health claims on the nutrient composition of single and subsequent meal servings. Appetite, 176, Article 106105. https://doi.org/10.1016/j.appet.2022.106105

Nutrition and health claims (NHCs) can help individuals make better food choices. While NHCs have been found to influence consumer perceptions and consumption, there has been less focus on how claims influence the nutritional composition of servings.... Read More about The effects of nutrition and health claims on the nutrient composition of single and subsequent meal servings.

Intermediate Variable Emulation: using internal processes in simulators to build more informative emulators (2022)
Journal Article
Oughton, R., Goldstein, M., & Hemmings, J. (2022). Intermediate Variable Emulation: using internal processes in simulators to build more informative emulators. SIAM/ASA Journal on Uncertainty Quantification, 10(1), 268-293. https://doi.org/10.1137/20m1370902

Complex systems are often modelled by intricate and intensive computer simulators. This makes their behaviour difficult to study, and so a statistical representation of the simulator is often used, known as an emulator, to enable users to explore the... Read More about Intermediate Variable Emulation: using internal processes in simulators to build more informative emulators.

A sequential dynamic Bayesian network for pore pressure estimation with uncertainty quantification (2017)
Journal Article
Oughton, R. H., Wooff, D. A., Hobbs, R. W., Swarbrick, R. E., & O'Connor, S. A. (2018). A sequential dynamic Bayesian network for pore pressure estimation with uncertainty quantification. Geophysics, 83(2), D27-D39. https://doi.org/10.1190/geo2016-0566.1

Pore-pressure estimation is an important part of oil-well drilling, since drilling into unexpected highly pressured fluids can be costly and dangerous. However, standard estimation methods rarely account for the many sources of uncertainty, or for th... Read More about A sequential dynamic Bayesian network for pore pressure estimation with uncertainty quantification.

A study of non-linearity in rainfall-runoff response using 120 UK catchments (2016)
Journal Article
Mathias, S., McIntyre, N., & Oughton, R. (2016). A study of non-linearity in rainfall-runoff response using 120 UK catchments. Journal of Hydrology, 540, 423-436. https://doi.org/10.1016/j.jhydrol.2016.06.039

This study presents a catchment characteristic sensitivity analysis concerning the non-linearity of rainfall-runoff response in 120 UK catchments. Two approaches were adopted. The first approach involved, for each catchment, regression of a power-law... Read More about A study of non-linearity in rainfall-runoff response using 120 UK catchments.

Hierarchical Emulation: a method for modeling and comparing nested simulators (2016)
Journal Article
Oughton, R. H., & Craig, P. S. (2016). Hierarchical Emulation: a method for modeling and comparing nested simulators. SIAM/ASA Journal on Uncertainty Quantification, 4(1), 495-519. https://doi.org/10.1137/15m1007914

Computer simulators often contain options to include extensions, leading to different versions of a particular simulator with slightly different input spaces. We develop hierarchical emulation, a method for emulating such simulators and for learning... Read More about Hierarchical Emulation: a method for modeling and comparing nested simulators.

Quantifying uncertainty in pore pressure estimation using Bayesian networks, with application to use of an offset well (2015)
Report
Oughton, R., Wooff, D., Hobbs, R., O'Connor, S., & Swarbrick, R. (2015). Quantifying uncertainty in pore pressure estimation using Bayesian networks, with application to use of an offset well. [No known commissioning body]

Pore pressure estimation is a crucial yet difficult problem in the oil industry. If unexpected overpressure is encountered while drilling it can result in costly challenges and leaked hydrocarbons. Prediction methods often use empirical porosity-base... Read More about Quantifying uncertainty in pore pressure estimation using Bayesian networks, with application to use of an offset well.

Modelling Uncertainty in Pore Pressure Using Dynamic Bayesian Networks (2015)
Presentation / Conference Contribution
Oughton, R., Wooff, D., Swarbrick, R., & Hobbs, R. (2015, June). Modelling Uncertainty in Pore Pressure Using Dynamic Bayesian Networks. Presented at 77th EAGE Conference & Exhibition 2015 : Earth Science for Energy and Environment., Madrid, Spain

Pore pressure prediction is vital when drilling a well, as unexpected overpressure can cause drilling challenges and uncontrolled hydrocarbon leakage. Predictions often use porosity-based techniques, relying on an idealised compaction trend and using... Read More about Modelling Uncertainty in Pore Pressure Using Dynamic Bayesian Networks.

A Bayesian shifting method for uncertainty in the open-hole gamma-ray log around casing points (2014)
Journal Article
Oughton, R. H., Wooff, D. A., & O'Connor, S. A. (2014). A Bayesian shifting method for uncertainty in the open-hole gamma-ray log around casing points. Petroleum Geoscience, 20(4), 375-391. https://doi.org/10.1144/petgeo2014-006

The wireline gamma-ray log is sensitive to open-hole conditions and, in particular, the diameter. This means that the log can jump at casing points. Although environmental corrections exist, they can fail at these points. We present a Bayesian method... Read More about A Bayesian shifting method for uncertainty in the open-hole gamma-ray log around casing points.