Reconciling Cover Thickness Estimates in Cloncurry Region in Queensland, Australia using Bayesian Estimate Fusion

2020 ◽  
Author(s):  
Jelena Markov ◽  
Gerhard Visser
Keyword(s):  
Mineral Exploration ◽  
Optimal Solution ◽  
Geophysical Data ◽  
Bayesian Estimate ◽  
Mount Isa ◽  
History Of ◽  
Cover Thickness ◽  
Inference Methods ◽  
Drill Holes ◽  
Fault Information

<p>The Cloncurry region lies in NW of Queensland and includes the Mount Isa Inlier, one of the most highly endowed metallogenic provinces in Australia, which has a long history of mining and exploration. The area is covered by the Jurassic-Cretaceous Carpentaria and Eromanga Basin sediments with the Mount Isa Inlier outcropping to the West and South. The fully concealed Millungera Basin underlies younger basins to the East. In order to de-risk further mineral exploration in this region it is important to know the thickness of cover. There are a variety of geophysical data available that can be used to estimate cover thickness. The point depth estimates of cover are derived from geophysical data using different inference methods. In order to create a map, these individual depth estimates must be reconciled/interpolated. The conventional interpolation methods do not produce the most optimal solution since these methods don’t easily account for discrepancies in the geophysical data distribution, resolution of the data and consequently variable accuracy of the cover thickness depth estimates. Also, most of these techniques do not produce an uncertainty estimate of the result. We have developed a Bayesian estimate fusion method that accounts for the variable data inaccuracies of the point cover thickness estimates which produces a map of cover thickness and its uncertainty. Additionally, the method uses non-intersecting drill holes, which were not usually utilised to create a map of the cover thickness. The method deals with outliers, by differentiating between the point depth estimates related to the cover-basement interface and the false positives that might be coming from the intrasedimentary units or the deeper basement. Lastly, the method incorporates existing fault information which allows to better capture sharp cover thickness changes.</p>

Cover thickness uncertainty mapping using Bayesian estimate fusion: leveraging domain knowledge

2019 ◽  
Vol 219 (3) ◽  
pp. 1474-1490 ◽  
Author(s):  
Gerhard Visser ◽  
Jelena Markov
Keyword(s):  
Domain Knowledge ◽  
Mineral Exploration ◽  
Synthetic Data ◽  
Drill Hole ◽  
Geophysical Data ◽  
Bayesian Estimate ◽  
Data Types ◽  
Interpolation Methods ◽  
Uncertainty Mapping ◽  
Cover Thickness

SUMMARY Thickness of cover over crystalline basement is an important consideration for mineral exploration in covered regions. It can be estimated from a variety of geophysical data types using a variety of inference methods. A robust method for combining such estimates to map the cover–basement interface over a region of interest is needed. Due to the large uncertainties involved, these need to be probabilistic maps. Predominantly, interpolation methods are used for this purpose, but these are built on simplifying assumptions about the inputs which are often inappropriate. The Bayesian estimate fusion is an alternative capable of addressing that issue by enabling more extensive use of domain knowledge about all inputs. This study is intended as a first step towards making the Bayesian estimate fusion a practical tool for cover thickness uncertainty mapping. The main contribution is to identify the types of data assumptions that are important for this problem, to demonstrate their importance using synthetic tests and to design a method that enables their use without introducing excessive tedium. We argue that interpolation methods like kriging often cannot achieve this goal and demonstrate that Markov chain Monte Carlo sampling can. This paper focuses on the development of statistical methodology and presents synthetic data tests designed to reflect realistic exploration scenarios on an abstract level. Intended application is for the early stages of exploration where some geophysical data are available while drill hole coverage is poor.

scholarly journals Inference of the worldwide invasion routes of the pinewood nematodeBursaphelenchus xylophilususing approximate Bayesian computation analysis

2018 ◽  
Author(s):  
Sophie Mallez ◽  
Chantal Castagnone ◽  
Eric Lombaert ◽  
Philippe Castagnone-Sereno ◽  
Thomas Guillemaud
Keyword(s):  
Approximate Bayesian Computation ◽  
Unknown Origin ◽  
Bayesian Computation ◽  
Pinewood Nematode ◽  
Invasion Routes ◽  
The Usa ◽  
History Of ◽  
Abc Method ◽  
Approximate Bayesian ◽  
Inference Methods

ABSTRACTPopulation genetics have been greatly beneficial to improve knowledge about biological invasions. Model-based genetic inference methods, such as approximate Bayesian computation (ABC), have brought this improvement to a higher level and are now essential tools to decipher the invasion routes of any invasive species. In this paper, we performed ABC analyses to shed light on the pinewood nematode (PWN) worldwide invasion routes and to identify the source of European populations. Originating from North America, this microscopic worm has been invading Asia since 1905 and Europe since 1999, causing tremendous damage on pine forests. Using microsatellite data, we demonstrated the existence of multiple introduction events in Japan (one involving individuals originating from the USA and one involving individuals with an unknown origin) and China (one involving individuals originating from the USA and one involving individuals originating from Japan). We also found that Portuguese samples had an American origin. Although we observed some discrepancies between descriptive genetic methods and the ABC method, which are worth investigating and are discussed here, the ABC approach definitely helped clarify the worldwide history of the PWN invasion.

Estimation Update and Feedback Procedures

2008 ◽  
Author(s):  
P.J. Lee
Keyword(s):  
Water Saturation ◽  
Geophysical Data ◽  
Source Rocks ◽  
Geochemical Data ◽  
Burial History ◽  
Data Types ◽  
Petroleum Resource ◽  
History Of ◽  
Seismic Sections ◽  
Well Data

A basin or subsurface study, which is the first step in petroleum resource evaluation, requires the following types of data: • Reservoir data—pool area, net pay, porosity, water saturation, oil or gas formation volume factor, in-place volume, recoverable oil volume or marketable gas volume, temperature, pressure, density, recovery factors, gas composition, discovery date, and other parameters (refer to Lee et al., 1999, Section 3.1.2). • Well data—surface and bottom well locations; spud and completion dates; well elevation; history of status; formation drill and true depths; lithology; drill stem tests; core, gas, and fluid analyses; and mechanical logs. • Geochemical data—types of source rocks, burial history, and maturation history. • Geophysical data—prospect maps and seismic sections. Well data are essential when we construct structural contour, isopach, lithofacies, porosity, and other types of maps. Geophysical data assist us when we compile number-of-prospect distributions and they provide information for risk analysis.

Regolith Science

2009 ◽  
Keyword(s):  
Mineral Exploration ◽  
Soil Science ◽  
Research Centre ◽  
Cooperative Research ◽  
Postgraduate Students ◽  
Elemental Abundances ◽  
History Of ◽  
Sulfate Soils ◽  
Unpublished Information ◽  
Comprehensive Reference

This comprehensive reference on the fundamentals of regolith geoscience describes how regolith is developed from parental rocks and emphasises the importance of chemical, physical, water and biological processes in regolith formation. It provides details for mapping regolith landforms, as well as objective information on applications in mineral exploration and natural resource management. Regolith Science also provides a concise history of weathering through time in Australia. It includes previously unpublished information on elemental abundances in regolith materials along with detailed information on soil degradation processes such as acid sulfate soils. Written by experts in the field, Regolith Science summarises research carried out over a 13-year period within the Cooperative Research Centre for Landscape Environments and Mineral Exploration. This book will be a valuable resource for scientists and graduate/postgraduate students in geology, geography and soil science, professionals in the exploration industry and natural resources management. This paperback edition is a reprint of the original hardback published in October 2008.

scholarly journals Parameter Identification of the Vortex-Induced Vertical Force Model Using a New Adaptive PSO

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Xiaoxia Tian ◽  
Jingwen Yan ◽  
Chi Xiao
Keyword(s):  
Optimal Solution ◽  
Time History ◽  
Vertical Displacement ◽  
Force Model ◽  
Vertical Force ◽  
Inertia Weight ◽  
Adaptive Pso ◽  
Short Run ◽  
History Of ◽  
Searching Ability

The paper proposes a new adaptive PSO (NAPSO) that adaptively adjust the inertial weight of every particle according to its own current fitness. In NAPSO, the searching ability of each particle is controlled by the inertial weight. In pursuit of the optimal solution, if a particle has a rather small value of normalized fitness, it has a small inertia weight so as to increase local searching ability; on the contrary, it has a large inertia weight to increase global searching ability. Simulation results include three parts: the NAPSO shows fast convergence and good stability compared with other PSOs; the NAPSO shows good fit and short run-time compared with GA and GALMA; according to the identified parameters, the time history of predicted vertical displacement is quite in accordance with the time history of measured displacement. As far as the nonlinear VIVF model is concerned, the NAPSO is a simple and effective identification method.

Variations of fluvial patterns and infilling history of a paleoincised valley system during Late Pleistocene to Holocene, Offshore Pahang River, Peninsular Malaysia

2018 ◽  
Vol 6 (1) ◽  
pp. T39-T50
Author(s):  
Md Mostafizur Rahman ◽  
Edlic Sathiamurthy ◽  
Guangfa Zhong ◽  
Jianghua Geng ◽  
Zhifei Liu
Keyword(s):  
Sea Level ◽  
Late Pleistocene ◽  
Peninsular Malaysia ◽  
Glacial Cycle ◽  
Shallow Marine ◽  
3D Data ◽  
Data Volume ◽  
History Of ◽  
Late Pleistocene To Holocene ◽  
Cover Thickness

High-resolution 2D acoustic profiles, combined with time slices from a 3D data volume, were used to investigate the paleoincised valleys offshore of the present-day Pahang River, South China Sea. Paleovalleys were formed during the regressive phase of the last glacial cycle. They were submerged and possibly filled during valley formation and postglacial marine transgression. Interpretation of acoustic profiles illustrates that the valleys were incised and infilled during the regression and low stand followed by subsequent deglacial sea-level rise. They were overlain by a transgressive ravinement surface suggesting transitional deposits between fluvial-dominated filling and shallow-marine deposition. This ravinement surface is overlain by Holocene shallow marine deposits. A low-sinuosity low-stand valley system changed to a high-sinuosity meander belt and eventually evolved into a deltaic distributary channel system before the complete submergence of the area. The average Late Pleistocene surface lies between 53 and 64 m below present-day mean sea level in the study area with approximately 16–50 m of valley incision. The Holocene shallow marine cover thickness varies from 5 to 10 m.

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