2019 ◽  
Vol 4 (2) ◽  
pp. 82
Author(s):  
Beny Wiranata ◽  
Hendra Amijaya ◽  
Ferian Anggara ◽  
Agung Rizki Perdana ◽  
Oyinta Fatma Isnadiyati ◽  
...  

Tanjung Formation is one of the major coal-bearing deposit in the Barito Basin, Central Kalimantan. The distribution of total sulfur and ash yield in coal is closely related to the depositional environment. This study was to determine the total sulfur and ash yield and the interpretation of the dynamics of depositional process. Coal seam A and B generally have low to medium ash yield 2.82 to 9.23 (wt.%, db) and low total sulfur content of <1 (wt.%, db), except for the 6PLY1 coal sample which has total sulfur content that relatively high at 1.55 (wt.%, db). Coal samples 5PLY1A, 5PLY1B, 5PLY3, 5PLY5, 6PLY2, 6PLY4, 6PLY5, 6PLY7, and 6PLY9 which have low to medium ash yield and low total sulfur content <1% (wt.%, db) are formed in the topogeneous mire (freshwater swamp) in a fluvial environment. The total sulfur content was interpreted to be derived mainly from the parent plant materials. Meanwhile, the 6PLY1 coal sample which has an ash yield of 5.83 (wt.%, db) and total sulfur content of 1.55 (wt.%, db) formed in topogeneous mire in an environment that is invaded by sea water, and the total sulfur content were interpreted coming from the parent plant materials and the effect of seawater invasion which is rich in sulfate (SO4) compounds. It is also supported by the occurrence of syngenetic mineral content (framboidal pyrite) and epigenetic pyrite of 1.23 (vol.%).


2020 ◽  
Author(s):  
Daniel Collins ◽  
Alexandros Avdis ◽  
Martin R. Wells ◽  
Andrew J. Mitchell ◽  
Peter Allison ◽  
...  

This review demonstrates the benefit of numerical tidal modelling, calibrated by integrated comparison to the preserved stratigraphic record, and offers a refined classification and prediction of shoreline process regimes. Wider and consistent utilisation of these concepts, and numerical simulations of other depositional processes, will further improve process-based classifications and predictions of modern and ancient shoreline systems.


2021 ◽  
Author(s):  
Haibin Di ◽  
Chakib Kada Kloucha ◽  
Cen Li ◽  
Aria Abubakar ◽  
Zhun Li ◽  
...  

Abstract Delineating seismic stratigraphic features and depositional facies is of importance to successful reservoir mapping and identification in the subsurface. Robust seismic stratigraphy interpretation is confronted with two major challenges. The first one is to maximally automate the process particularly with the increasing size of seismic data and complexity of target stratigraphies, while the second challenge is to efficiently incorporate available structures into stratigraphy model building. Machine learning, particularly convolutional neural network (CNN), has been introduced into assisting seismic stratigraphy interpretation through supervised learning. However, the small amount of available expert labels greatly restricts the performance of such supervised CNN. Moreover, most of the exiting CNN implementations are based on only amplitude, which fails to use necessary structural information such as faults for constraining the machine learning. To resolve both challenges, this paper presents a semi-supervised learning workflow for fault-guided seismic stratigraphy interpretation, which consists of two components. The first component is seismic feature engineering (SFE), which aims at learning the provided seismic and fault data through a unsupervised convolutional autoencoder (CAE), while the second one is stratigraphy model building (SMB), which aims at building an optimal mapping function between the features extracted from the SFE CAE and the target stratigraphic labels provided by an experienced interpreter through a supervised CNN. Both components are connected by embedding the encoder of the SFE CAE into the SMB CNN, which forces the SMB learning based on these features commonly existing in the entire study area instead of those only at the limited training data; correspondingly, the risk of overfitting is greatly eliminated. More innovatively, the fault constraint is introduced by customizing the SMB CNN of two output branches, with one to match the target stratigraphies and the other to reconstruct the input fault, so that the fault continues contributing to the process of SMB learning. The performance of such fault-guided seismic stratigraphy interpretation is validated by an application to a real seismic dataset, and the machine prediction not only matches the manual interpretation accurately but also clearly illustrates the depositional process in the study area.


2019 ◽  
Vol 5 (5) ◽  
pp. eaav5891 ◽  
Author(s):  
C. Kusebauch ◽  
S. A. Gleeson ◽  
M. Oelze

The giant Carlin-type Au deposits (Nevada, USA) contain gold hosted in arsenic-rich iron sulfide (pyrite), but the processes controlling the sequestration of Au in these hydrothermal systems are poorly understood. Here, we present an experimental study investigating the distribution of Au and As between hydrothermal fluid and pyrite under conditions similar to those found in Carlin-type Au deposits. We find that Au from the fluid strongly partitions into a newly formed pyrite depending on the As concentration and that the coupled partitioning behavior of these two trace elements is key for Au precipitation. On the basis of our experimentally derived partition coefficients, we developed a mass balance model that shows that simple partitioning (and the underlying process of adsorption) is the major depositional process in these systems. Our findings help to explain why pyrite in Carlin-type gold deposits can scavenge Au from hydrothermal fluids so efficiently to form giant deposits.


2008 ◽  
Vol 12 (4) ◽  
pp. 93
Author(s):  
M Durand ◽  
J C Abrahams

Diffuse signal changes in the liver on MRI often represent a depositional process with decreased signal when iron or copper is deposited or increased signal with fatty deposition. We present a 68y male with myelodysplasia requiring multiple blood transfusion, resulting in such signal changes.


2014 ◽  
Vol 51 (8) ◽  
pp. 844-857 ◽  
Author(s):  
S. Firouzianbandpey ◽  
D.V. Griffiths ◽  
L.B. Ibsen ◽  
L.V. Andersen

The main topic of this study is to assess the anisotropic spatial correlation lengths of a sand layer deposit based on cone penetration testing with pore pressure measurement (CPTu) data. Spatial correlation length can be an important factor in reliability analysis of geotechnical systems, yet it is rarely estimated during routine site investigations. Results from two different sites in the north of Denmark are reported in this paper, indicating quite strong anisotropy due to the depositional process, with significantly shorter spatial correlation lengths in the vertical direction. It is observed that the normalized cone resistance is a better estimator of spatial trends than the normalized friction ratio.


1992 ◽  
Vol 129 (5) ◽  
pp. 567-572 ◽  
Author(s):  
T. K. Ball ◽  
J. R. Davies ◽  
R. A. Waters ◽  
J. A. Zalasiewicz

AbstractA preliminary geochemical investigation of Silurian (Llandovery) basinal mudstones (turbidites and hemipelagites) from the Southern Welsh Basin is described. Turbidite mudstones show higher concentrations of Fe2O3, MgO, TiO2, MnO, LOI, Zn and Zr than laminated hemipelagites. This is consistent with the observed higher concentrations of chlorite and Ti-bearing minerals in turbidite mudstones. Laminated hemipelagites show higher values of REEs (Ce and La), concentrated within authigenic monazites, and Ni, As, Cu and Pb within sulphide minerals (pyrite and galena) reflecting the influence of primary organic carbon levels and anoxic bottom waters on early diagenesis. Deposition of hemipelagites under oxidizing conditions is reflected in lower concentrations of authigenic sulphide mineral hosted elements compared with laminated hemipelagic lithologies. There is a distinct geochemical difference between mudstones of easterly and southerly provenance in the Southern Welsh Basin. This is shown for both turbidites and hemipelagites. The differences are due to the increased input of illite and the chemical elements associated with this mineral (K2O, A12O3, Rb and Ba). Turbidite mudstones sourced from the south show increased levels of heavy minerals, especially those associated with Ti-rich minerals. There is also an increase in elements associated with detrital monazites: Th and Y. The hemipelagites show higher values of REE and chalcophile elements consistent with their more reduced nature.


1967 ◽  
Vol 7 (03) ◽  
pp. 243-251 ◽  
Author(s):  
Paul Edwin Potter ◽  
Robert F. Blakely

Abstract Any stratigraphic section or bedding sequence can be synthesized if there is a transition procedure from one lithology or bedding type to another, and if thickness distributions of the different lithologies are known. Stratigraphic sections of a fluvial sandstone body were synthesized with five bedding types: cross-bedding, massive beds, parting lineation, ripple mark and mudstone. The transition procedure from one bedding type to another used dependent, Markovian random processes which have a memory that extends one step backward in the depositional process. As observed in nature, median grain size and sand wave thickness (cross-bedding and ripple mark) decline upward in the synthesized sections as proportions of the different bedding types change. Grain size and permeability were also incorporated into the sections. By changing the transition procedures, bed thickness distributions, rate of upward decline or sand wave height and length, different types of sections can be synthesized, thus making it possible to model many different sedimentation problems. Introduction This paper describes a general method for synthesizing stratigraphic sections and bedding sequences of sedimentary, metamorphic or igneous origin. Synthetic generation is of interest for several reasons. Close correspondence between real and synthetic sections suggest that the factors used in the synthesizing model may indeed be the correct ones, thus giving the investigator a check on his assumptions. Rapid, inexpensive simulation of many stratigraphic sections permits one to synthesize a rock body (sandstone or carbonate reservoir) or, on a larger scale, the fill of a sedimentary basin. Harbaugh gives an example of mathematical simulation of a carbonate basin. He simulated the basin in the hope that improved prediction would follow better understanding of the depositional processes. From the petroleum engineer's viewpoint it seems reasonable to believe that the synthetic generation of rock properties and their distribution in a reservoir should be relevant in the study of reservoirs. Any stratigraphic section or bedding sequence can be generated provided there is a transition procedure from one lithology or bedding type to another and provided the thickness distributions of the different units are known. The transition procedure involves random processes that are either independent or dependent. If the depositional process is independent, previous deposition will have no influence on present deposition. However, if it is dependent, past deposition will influence either present or future deposition. Such a dependent depositional process can be thought of as having a memory that extends backward in time through one or more pulses of deposition. A process with a memory can be described by a Markov process. Because the concept of memory or dependence appears to be in accord with our understanding of many depositional processes, Markov processes were used to synthesize the bedding sequences of this study (see Appendix). The above methods are perfectly general and are appropriate for any stratigraphic section or bedding sequence: bedding types in a beach deposit, an evolving carbonate bank or the changing lithologic fill of a thick geosyncline sequence. We chose to synthesize a vertical profile of a fluvial sandstone body because its characteristics were well documented, much was known about fluvial processes and fluvial-deltaic sandstone bodies constitute an important class of petroleum reservoirs. CHARACTERISTICS AND ORIGIN OF FLUVIAL CYCLE The fluvial cycle has been well documented in recent years by Bersier, Allen and Visher. Deposits from fluvial cycles range from 10 to 150 ft or more in thickness and are characterized by a "fining upwards": coarse sandstones with occasional conglomerates grade upward into medium- to fine-grained sandstone, and hence into siltstone and mudstone. SPEJ P. 243ˆ


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