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A Bayesian multi-region radial composite reservoir model for deconvolution in well test analysis (2022)
Journal Article
Botsas, T., Cumming, J., & Jermyn, I. (2022). A Bayesian multi-region radial composite reservoir model for deconvolution in well test analysis. Journal of the Royal Statistical Society: Series C, 71(4), 951-968. https://doi.org/10.1111/rssc.12562

In petroleum well test analysis, deconvolution is used to obtain information about the reservoir system. This information is contained in the response function, which can be estimated by solving an inverse problem in the pressure and flow rate measur... Read More about A Bayesian multi-region radial composite reservoir model for deconvolution in well test analysis.

Estimating Exposure Fraction from Radiation Biomarkers: A Comparison of Frequentist and Bayesian Approaches (2021)
Book Chapter
Errington, A., Einbeck, J., & Cumming, J. (2021). Estimating Exposure Fraction from Radiation Biomarkers: A Comparison of Frequentist and Bayesian Approaches. In M. Vasile, & D. Quagliarella (Eds.), Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications (393-405). Springer Verlag. https://doi.org/10.1007/978-3-030-80542-5_24

If individuals are exposed to ionising radiation, due to some radiation accident, for medical reasons, or during spaceflight, there is often a need to estimate the contracted radiation dose. The field of biodosimetry is concerned with estimating the... Read More about Estimating Exposure Fraction from Radiation Biomarkers: A Comparison of Frequentist and Bayesian Approaches.

The effect of data aggregation on dispersion estimates in count data models (2021)
Journal Article
Errington, A., Einbeck, J., Cumming, J., Rössler, U., & Endesfelder, D. (2022). The effect of data aggregation on dispersion estimates in count data models. International Journal of Biostatistics, 18(1), 183-202. https://doi.org/10.1515/ijb-2020-0079

For the modelling of count data, aggregation of the raw data over certain subgroups or predictor configurations is common practice. This is, for instance, the case for count data biomarkers of radiation exposure. Under the Poisson law, count data can... Read More about The effect of data aggregation on dispersion estimates in count data models.

Bayes Linear Emulation of Simulated Crop Yield (2021)
Book Chapter
Hasan, M. M., & Cumming, J. A. (2021). Bayes Linear Emulation of Simulated Crop Yield. In Y. P. Chaubey, S. Lahmiri, F. Nebebe, & A. Sen (Eds.), Applied Statistics and Data Science:Proceedings of Statistics 2021 Canada, Selected Contributions (145-151). Springer Verlag. https://doi.org/10.1007/978-3-030-86133-9_7

The analysis of the output from a large-scale computer simulation experiment can pose a challenging problem in terms of size and computation. We consider output in the form of simulated crop yields from the Environmental Policy Integrated Climate (EP... Read More about Bayes Linear Emulation of Simulated Crop Yield.

A Bayesian non-linear hierarchical framework for crop models based on big data outputs (2020)
Presentation / Conference Contribution
Hasan, M. M., & Cumming, J. (2020, December). A Bayesian non-linear hierarchical framework for crop models based on big data outputs. Paper presented at 13th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2020), King's College London, England

Assessing the Non-Uniqueness of a Well Test Interpretation Model Using a Bayesian Approach (2020)
Presentation / Conference Contribution
Cumming, J., Botsas, T., Jermyn, I., & Gringarten, A. (2020, December). Assessing the Non-Uniqueness of a Well Test Interpretation Model Using a Bayesian Approach. Presented at SPE Virtual Europec 2020

Objectives/Scope: A stable, single-well deconvolution algorithm has been introduced for well test analysis in the early 2000’s, that allows to obtain information about the reservoir system not always available from individual flow periods, for exampl... Read More about Assessing the Non-Uniqueness of a Well Test Interpretation Model Using a Bayesian Approach.

Statistical Approach to Raman Analysis of Graphene-Related Materials: Implications for Quality Control (2020)
Journal Article
Goldie, S. J., Bush, S., Cumming, J. A., & Coleman, K. S. (2020). Statistical Approach to Raman Analysis of Graphene-Related Materials: Implications for Quality Control. ACS Applied Nano Material, 3(11), 11229-11239. https://doi.org/10.1021/acsanm.0c02361

A statistical method to determine the number of measurements required from nanomaterials to ensure reliable and robust analysis is described. Commercial products utilizing graphene are in their infancy and recent investigations of commercial graphene... Read More about Statistical Approach to Raman Analysis of Graphene-Related Materials: Implications for Quality Control.

Constrained Least-Squares Multiwell Deconvolution (2019)
Presentation / Conference Contribution
Cumming, J., Jaffrezic, V., Whittle, T., & Gringarten, A. (2019, August). Constrained Least-Squares Multiwell Deconvolution. Presented at SPE Western Regional Meeting, San Jose, California, USA

In this paper, we reduce non-uniqueness and ensure physically feasible results in multiwell deconvolution by incorporating constraints and knowledge to the methodology of Cumming et al. (2014). The constraints discourage non-physical shapes for the d... Read More about Constrained Least-Squares Multiwell Deconvolution.

Field Applications of Constrained Multiwell Deconvolution (2019)
Presentation / Conference Contribution
Jaffrezic, V., Razminia, K., Cumming, J., & Gringarten, A. (2019, December). Field Applications of Constrained Multiwell Deconvolution. Presented at SPE Europec featured at 81st EAGE Conference and Exhibition, London, UK