In a geological study, an important step is to determine the type of sedimentary rock or its grain size. Such a determination requires accurate analysis in the field or in a laboratory. As the size of the study area grows, this activity can be time consuming and error prone because the number of specialists working under rigid criteria also increases. This paper proposes a novel methodology to classify grain size using unique wavelength reflectance data and artificial neural networks. The results indicate that the proposed method can be reliably used in the field.

Artificial neural network–based method to classify sedimentary rocks

Optical characteristics of sedimentary rocks and their constituent minerals are routinely observed and quantified with the petrographic (polarizing) microscope and reported in the literature; a quantitative acoustic examination at comparable magnification (i.e., about 85 times) is reported here for the first time. The ultrasonic velocities of selected individual grains of quartz and feldspar are presented and compared with published values for these minerals obtained using macroscopic techniques. Qualitative interpretations of the acoustic photomicrographs include an examination of silicate minerals (quartz, feldspar), sedimentary rocks (sandstone. mudstone), and some common features of sedimentary rocks (laminar, bedding, pores, cement, fractures). A comparison of acoustic and optical characteristics of specific features, such as twinning and fractures of sedimentary rocks and minerals is made.

An Examination of Sedimentary Rocks and Constituent Minerals with the Scanning Laser Acoustic Microscope

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

J. Brown

Author Tools

Chat about Author

Papers

An Examination of Sedimentary Rocks and Constituent Minerals with the Scanning Laser Acoustic Microscope