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Conference paperNorth TL, Muxworthy AR, Collins GS, et al., 2022,
THERMOREMANENT MAGNETISATION RECORDED DURING IMPACT-INDUCED COMPACTION EXPERIMENTS ON SYNTHETIC CHONDRITIC METEORITES, LSPC, Publisher: WILEY, ISSN: 1086-9379
Journal articleAbdulkarim MA, Muxworthy A, Fraser A, et al., 2022,
Effect of hydrocarbon presence and properties on the magnetic signature of the reservoir sediments of the Catcher Area Development (CAD) region, UK North Sea, Frontiers in Earth Science, Vol: 10, Pages: 1-20, ISSN: 2296-6463
This paper presents a detailed study investigating the effect of hydrocarbon presence on magnetic mineral diagenesis in sediments from the Catcher Area Development (CAD) region, UK North Sea, between 1,000 and 1,500 m (True Vertical Depth Sub-Sea). Magnetic analysis of core samples from hydrocarbon fields of the region and nearby dry-well sandstones (background) was carried out to determine if their signatures can serve as a proxy for understanding petroleum reservoir systems. From the background samples, nanometric and micron-sized magnetite, hematite and titano-iron oxides, were identified. Hydrocarbon presence in the reservoir sediments was found to diminish the iron-oxide signature and favour the precipitation of hexagonal pyrrhotite, siderite and potentially vivianite, lepidocrocite, greigite and paramagnetic iron sulphides. Hexagonal pyrrhotite was found at the oil-water transition zones. This relationship is possibly related to biodegradation at this interface. Siderite was found in increased abundance at shallower depths within the reservoir, which we attribute to hydrocarbon vertical migration and biodegradation. The interbedded shales also experienced significant magnetic mineral diagenesis that depended on its proximity to the hydrocarbon plume. These findings suggest that mineral magnetism can be applied to the identification of oil-water transition zones, reserve estimation, production planning and the determination of hydrocarbon migration pathways. It also suggests that mineral magnetic methods can be used to estimate the timing of hydrocarbon migration.
Journal articleRoberts AP, Heslop D, Zhao X, et al., 2022,
Journal articleAbdulkarim M, Muxworthy A, Fraser A, et al., 2022,
Siderite occurrence in petroleum systems and its potential as a hydrocarbon-migration proxy: a case study of the Catcher Area Development and the Bittern area, UK North Sea, Journal of Petroleum Science and Engineering, ISSN: 0920-4105
Journal articleRoberts AP, Zhao X, Hu P, et al., 2021,
Magnetic domain state and anisotropy in hematite (alpha-Fe2O3) from first-order reversal curve diagrams, Journal of Geophysical Research. Solid Earth, ISSN: 2169-9356
Journal articleMuxworthy A, Baker E, 2021,
We report a new approach of implementing cooling-rate corrections in absolute ancient magnetic field intensity (paleointensity) studies. Nearly all methods of determining paleointensity estimates rely on rocks having recorded a thermoremanent magnetization (TRM), on cooling from above the rock’s constituent minerals’ Curie temperature. Typically paleointensity estimates are made by comparing natural TRM, with a TRM induced in the laboratory; however, TRM intensity has long been reported to be dependent on cooling rate. Natural cooling rates are impractical in laboratories. We have developed a new cooling-rate correction method and corresponding software (ThellierCoolPy), that directly corrects the unprocessed paleointensity data, using first-order reversal curve data collected on a sister sample. This site tailored cooling-rate correction has a unique correction for each temperature step within the paleointensity data set. This new method differs from previous approaches which apply a blanket cooling-rate correction independent of the material properties of the sample. Paleointensity data from historical lavas from Parícutin, Mexico, are used to demonstrate the new software. For this data set, it is shown that cooling time of 1 million years yields a reduction of the paleointensity of ∼7%. The software is available for download.
Journal articleNoble JPP, Bending SJ, Sartbaeva A, et al., 2021,
Journal articleBadejo SA, Muxworthy A, Fraser A, et al., 2021,
Identifying the depths of the hydrocarbon-fluid contacts in a reservoir is important for determining hydrocarbon reserves and production planning. Using core samples from the Tay sandstone reservoir in the Central North Sea, we show that thereis a magnetic enhancement at the hydrocarbon-fluid contacts, that is detectable both through magnetic susceptibility measurements and magnetic hysteresis measurements. We observed this magnetic enhancement at both gas-oil and oil-water contacts, that have been independently identified using non-magnetic methods; we did not consider gas-water contacts in this study. We demonstrate that this magnetic enhancement is due to the precipitation of new nanometric iron oxide (magnetite) and iron sulphide (greigite)phases. The magnetic enhancement may be caused by diagenetic changes or preferential biodegradation at the top of the oil column during early filling and at the oil water contact. Our findings have the potential to be used to identify paleo-hydrocarbon-fluid contact in both structurally modified fields and failed wells. The technique can also be used to infer the fill history of a basin and calibrate petroleum systems models. Magnetic susceptibility measurements have the advantage that they can easily and quickly be measured in the field on whole core-material.
Journal articleBadejo SA, Muxworthy AR, Fraser A, et al., 2021,
Using magnetic techniques to calibrate hydrocarbon migration in petroleum systems modelling: A Case Study from the Lower Tertiary, UK Central North Sea, Geophysical Journal International, Vol: 227, Pages: 617-631, ISSN: 0956-540X
Magnetic minerals form or alter in the presence of hydrocarbons, making them a potential magnetic proxy for identifying hydrocarbon migration pathways. In this paper, we test this idea by magnetically measuring core samples from the Tay Fan in the Western Central Graben in the Central North Sea. In a companion paper, 3-D petroleum systems modelling has been carried out to forward model migration pathways within the Tay Fan. Rock magnetic experiments identified a range of magnetite, maghemite, iron sulphides, siderite, goethite and titanohematite, some of which are part of the background signal, and some due to the presence of hydrocarbons. Typical concentrations of the magnetic minerals were ∼10–200 ppm. Importantly, we have identified an increasing presence of authigenic iron sulphides (likely pyrite and greigite) along the identified lateral hydrocarbon migration pathway (east to west). This is likely caused by biodegradation resulting in the precipitation of iron sulphides, however, though less likely, it could alternatively be caused by mature oil generation, which subsequently travelled with the migrating oil to the traps in the west. These observations suggest mineral magnetic techniques could be a rapid alternative method for identifying the severity of biodegradation or oil maturity in core sample, which can then be used to calibrate petroleum systems models.
Journal articleBadejo S, Fraser A, Neumaier M, et al., 2021,
3D Petroleum Systems Modelling as an exploration tool in mature basins: A study from the Central North Sea, UK., Marine and Petroleum Geology, ISSN: 0264-8172
Journal articleHu P, Oda H, Zhao X, et al., 2020,
Assessment of magnetic techniques for understanding complex mixtures of magnetite and hematite: the Inuyama red chert, Journal of Geophysics Research - Solid Earth
Conference paperAbdulkarim M, Muxworthy A, Fraser A, et al., 2021,
PRECIPITATION OF SIDERITE IN HYDROCARBON ENVIRONMENT, Pages: 2417-2421
Migration of hydrocarbons in the subsurface has been shown to create an environment that promotes the precipitation and/or alteration of magnetic minerals. For example, iron oxides and iron sulphides have been shown to precipitate due to the reducing conditions created by hydrocarbon migration. Siderite, a paramagnetic mineral with Neel temperature of 37K has been variously identified in hydrocarbon environment and has also been suggested to be an authigenic product of hydrocarbon migration. However, it is commonly found in sedimentary settings. Here we show via experimental studies that siderite is precipitated due to hydrocarbon migrations and suggested the mechanism responsible for this process. Magnetic minerals precipitation along migration pathways suggests the creation of a magnetic fingerprint that if thoroughly understood can be applied to oil and gas exploration.
Journal articleChang L, Hong H, Bai F, et al., 2020,
Detrital remanent magnetization of single-crystal silicates with magnetic inclusions: constraints from deposition experiments, Geophysical Journal International, ISSN: 0956-540X
Journal articleZhang Y, Muxworthy A, Jia D, et al., 2020,
To better understand the fluid migration in orogenic zones and associated chemical remagnetization, we have conducted a detailed magnetic, petrographic, and strontium isotope study in an important orogenic belt of China, the Jurassic Dabashan fold and thrust belt. This belt formed by the continued collision of the North and South China blocks after the Late Triassic closure of the Paleo‐Tethys Ocean. Samples were collected in a variety of rock units of Ediacaran to Permian age, in both the thrust and the fold belts. Paleomagnetic analysis indicates that all the samples were remagnetized and carry a Middle‐Late Jurassic paleo‐direction. Rock magnetic data and scanning electron microscopy observations found that the proposed remagnetization is carried by framboidal magnetite, which likely formed by the replacement of pyrite. The pervasive nature of the chemical remagnetization in these units and belts and its temporal and spatial association with the orogeny suggest that it resulted from the alteration of orogeny‐induced fluids. Sr‐isotopic analysis of the units that are thought to be remagnetized suggests that the sediments in the thrust belt were altered by externally derived evolved fluids, whereas the Permian samples in the fold belt were altered by internal pore fluid mixing during the orogeny. Together with the lithological and structural features, we conclude that the external orogenic fluids migrated preferentially along thrust faults and unconformities but were blocked by layers of low‐permeability gypsum. Our results help to constrain the origin of widespread remagnetization in South China.
Journal articleHeslop D, Roberts AP, Oda H, et al., 2020,
First‐order reversal curve (FORC) distributions are a powerful diagnostic tool for characterizing and quantifying magnetization processes in fine magnetic particle systems. Estimation of FORC distributions requires the computation of the second‐order mixed derivative of noisy magnetic hysteresis data. This operation amplifies measurement noise, and for weakly magnetic systems, it can compromise estimation of a FORC distribution. Previous processing schemes, which are based typically on local polynomial regression, have been developed to smooth FORC data to suppress detrimental noise. Importantly, the smoothed FORC distribution needs to be consistent with the measurement data from which it was estimated. This can be a challenging task even for expert users, who must adjust subjectively parameters that define the form and extent of smoothing until a “satisfactory” FORC distribution is obtained. For nonexpert users, estimation of FORC distributions using inappropriate smoothing parameters can produce distorted results corrupted by processing artifacts, which can lead to spurious inferences concerning the magnetic system under investigation. We have developed a statistical machine learning framework based on a probabilistic model comparison to guide the estimation of FORC distributions. An intuitive approach is presented that reveals regions of a FORC distribution that may have been smoothed inappropriately. An associated metric can also be used to compare data preparation and local regression schemes to assess their suitability for processing a given FORC data set. Ultimately, our approach selects FORC smoothing parameters in a probabilistic fashion, which automates the derivative estimation process regardless of user expertise.
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