Alan Butcher

Prof. Alan Butcher

Circular Economy Solutions Unit, Circular Raw Materials Hub, Geological Survey of Finland, F1-02151 Espoo, Finland
orcid

Research Focus & Metrics

Academic Career Length

42Years (1985-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 September 2017 in Applied Energy
Verified
Journal Article
Open access
TSTarik Saif
Tarik Saif
QLQingyang Lin
Qingyang Lin
Alan ButcherAlan Butcher
Alan Butcher
BBBranko Bijeljic
Branko Bijeljic
MBMartin J. Blunt
Martin J. Blunt
The complexity of unconventional rock systems is expressed both in the compositional variance of the microstructure and the extensive heterogeneity of the pore space. Visualizing and quantifying the microstructure of oil shale before and after pyrolysis permits a more accurate determination of petrophysical properties which are important in modeling hydrocarbon production potential. We characterize the microstructural heterogeneity of oil shale using X-ray micro-tomography (µCT), automated ultra-high resolution scanning electron microscopy (SEM), MAPS Mineralogy (Modular Automated Processing System) and Focused Ion Beam Scanning Electron Microscopy (FIB-SEM). The organic-rich Eocene Green River (Mahogany zone) oil shale is characterized using a multi-scale multi-dimensional workflow both before and after pyrolysis. Observations in 2-D and 3-D and across nm-µm-mm length scales demonstrate both heterogeneity and anisotropy at every scale. Image acquisition and analysis using µCT and SEM reveal a microstructure of alternating kerogen-rich laminations interbedded with layers of fine-grained inorganic minerals. MAPS Mineralogy combined with ultrafast measurements reveal mineralogic textures dominated by dolomite, calcite, K-feldspar, quartz, pyrite and illitic clays along with their spatial distribution, augmenting conventional mineral analysis. From high resolution Backscattered electron (BSE) images, intra-organic, inter-organic-mineral, intra- and inter-mineral pores are observed with varying sizes and geometries. By using FIB milling and SEM imaging sequentially and repetitively, 3-D data sets were reconstructed. By setting 3-D gradient and marker-based watershed transforms, the organic matter, minerals and pore phases (including pore-back artifacts) were segmented and visualized and the pore-size distribution was computed. Following pyrolysis, fractures from the mm-to-µm scales were observed with preferential propagation along the kerogen-rich laminations and coalescence leading to an interconnected fracture network. The application of these techniques to worldwide oil shale deposits will allow significant insights into estimating mechanical and chemical proprieties of oil shale formations for modeling and designing oil shale pyrolysis processes

1 April 2000 in JOM
Verified
Journal Article
Closed access
PDF file
PGP. Gottlieb
P. Gottlieb
GWG. Wilkie
G. Wilkie
DSD. Sutherland
D. Sutherland
EHE. Ho-Tun
E. Ho-Tun
SSSteve Suthers
Steve Suthers
JRJ. Rayner
J. Rayner

1 January 2004 in Geological Society, London, Special Publications
Verified
Journal Article
Closed access
DPDuncan Pirrie
Duncan Pirrie
Alan ButcherAlan Butcher
Alan Butcher
MPMatthew R. Power
Matthew R. Power
PGPaul Gottlieb
Paul Gottlieb
GMGavin L. Miller
Gavin L. Miller
QemSCAN is a scanning electron microscope (SEM) system, initially designed to support the mining industry by providing rapid automated quantitative mineral analyses. The system is based upon Carl Zeiss SEMs fitted with up to four light-element energy dispersive X-ray spectrometers. Representative subsamples are mounted into either resin or wax blocks and polished prior to analysis, or can be mounted onto carbon tape. During analysis, X-ray spectra are collected at a user-defined pixel spacing and are acquired very rapidly ( c. 10 ms per pixel). The measured spectra are automatically compared against a database of known spectra and a mineral or phase name is assigned to each measurement point by the QemSCAN computer software programs. In this way the near-surface qualitative elemental composition of each particle is systematically mapped, assigned to a mineral name or chemical compound/species, and digital pixel maps of each particle are created. Depending upon a range of parameters, including the particle size and the user-defined pixel spacing (which can vary between 0.20 μm and 25 μm), approximately 1000 particles, each 1–10 μm in size, can be measured per hour using a 1 μm pixel spacing. In addition to providing a qualitative elemental analysis and mineralogical or phase assignment for each particle, data relating to particle size, shape and calculated specific density are also generated. In this study, the potential application of this automated SEM system in forensic geoscience was evaluated by the analysis of: (1) a series of soil samples, and (2) a series of dust samples from an industrial complex. In both case studies, the mine-ralogy/phase composition of each sample analysed was found to be distinctive. In addition, textural data for the soil samples and particle shape data for the dust samples show that they can be clearly distinguished. Automated SEM using QemSCAN has clear potential application in the analysis of soil or other trace evidence in forensic case work.

1 January 2018 in Geological Society, London, Special Publications
Verified
Journal Article
Open access
PDF file
RWRichard H. Worden
Richard H. Worden
PAP. J. Armitage
P. J. Armitage
Alan ButcherAlan Butcher
Alan Butcher
JCJ. M. Churchill
J. M. Churchill
ACA. E. Csoma
A. E. Csoma
JOJ. E. Omma
J. E. Omma
The porosity and permeability of sandstone and carbonate reservoirs (known as reservoir quality) are essential inputs for successful oil and gas resource exploration and exploitation. This chapter introduces basic concepts, analytical and modelling techniques and some of the key controversies to be discussed in 20 research papers that were initially presented at a Geological Society conference in 2014 titled ‘Reservoir Quality of Clastic and Carbonate Rocks: Analysis, Modelling and Prediction’. Reservoir quality in both sandstones and carbonates is studied using a wide range of techniques: log analysis and petrophysical core analysis, core description, routine petrographic tools and, ideally, less routine techniques such as stable isotope analysis, fluid inclusion analysis and other geochemical approaches. Sandstone and carbonate reservoirs both benefit from the study of modern analogues to constrain the primary character of sediment before they become a hydrocarbon reservoir. Prediction of sandstone and carbonate reservoir properties also benefits from running constrained experiments to simulate diagenetic processes during burial, compaction and heating. There are many common controls on sandstone and carbonate reservoir quality, including environment of deposition, rate of deposition and rate and magnitude of sea-level change, and many eogenetic processes. Compactional and mesogenetic processes tend to affect sandstone and carbonate somewhat differently but are both influenced by rate of burial, and the thermal and pressure history of a basin. Key differences in sandstone and carbonate reservoir quality include the specific influence of stratigraphic age on seawater composition (calcite v. aragonite oceans), the greater role of compaction in sandstones and the greater reactivity and geochemical openness of carbonate systems. Some of the key controversies in sandstone and carbonate reservoir quality focus on the role of petroleum emplacement on diagenesis and porosity loss, the role of effective stress in chemical compaction (pressure solution) and the degree of geochemical openness of reservoirs during diagenesis and cementation. This collection of papers contains case study-based examples of sandstone and carbonate reservoir quality prediction as well as modern analogue, outcrop analogue, modelling and advanced analytical approaches.

1 August 2010 in Marine and Petroleum Geology
Verified
Journal Article
Closed access
PAP.J. Armitage
P.J. Armitage
RWR.H. Worden
R.H. Worden
DFD.R. Faulkner
D.R. Faulkner
AAA.C. Aplin
A.C. Aplin
Alan ButcherAlan Butcher
Alan Butcher
JIJ. Iliffe
J. Iliffe

28 December 2011 in Journal of Geophysical Research
Verified
Journal Article
Closed access
PDF file
PAP. J. Armitage
P. J. Armitage
DFD. R. Faulkner
D. R. Faulkner
RWR. H. Worden
R. H. Worden
AAA. C. Aplin
A. C. Aplin
Alan ButcherAlan Butcher
Alan Butcher
JIJ. Iliffe
J. Iliffe