Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Application of Linearization and Approximation

Application of Linearization and Approximation

A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Molecular mechanism of allosteric modulation of opioid receptors.

Signal transduction and targeted therapy·2026

Same author

The role of YKL-40 in Alzheimer's disease pathology and drug targeting.

PeerJ·2026

Same author

Double-Sided Mechanical Interlocking Enables Soft-Rigid Conductive Interfaces With a Record High Toughness for Flexible Electronics.

Advanced materials (Deerfield Beach, Fla.)·2026

Same author

Observation on the clinical effects of four kinds of root canal filling materials in the treatment of chronic periapical periodontitis.

American journal of translational research·2026

Same author

The effect of yoga on birth outcomes of Chinese pregnancies with preeclampsia.

BMC pregnancy and childbirth·2026

Same author

Association of genetically determined plasma hepatocyte growth factor with lung cancer and its subtypes: Mendelian randomization and mediation analysis.

Medicine·2026

Same journal

Modeling and analysis of forward and inverse kinematics for a flexible Stewart platform.

PloS one·2026

Same journal

Barriers and facilitators to healthcare utilization amongst people living with sickle cell disease in the United States: A scoping review.

PloS one·2026

Same journal

Enhancing data completeness in time series: Imputation strategies for missing data using significant periodically correlated components.

PloS one·2026

Same journal

Key targets and mechanisms by which gut microbiota-derived metabolites regulate Alzheimer's disease through the immune - inflammatory pathway: Based on network pharmacology and molecular docking.

PloS one·2026

Same journal

Grid-tied Transformer-less Boost Switched Capacitor Topology (TLBSCT) for PV applications.

PloS one·2026

Same journal

The load-velocity profiles and exercise-specific velocity zones for seven commonly used weightlifting exercises.

PloS one·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 4, 2026

Reservoir Condition Pore-scale Imaging of Multiple Fluid Phases Using X-ray Microtomography

Reservoir Condition Pore-scale Imaging of Multiple Fluid Phases Using X-ray Microtomography

Published on: February 25, 2015

Study on automatic lithology identification method while drilling based on acoustic pressure-rock physics parameters

Wei Jiang^1,2, Qingfeng Wang^1,2,3, Baoyong Yan^1,2

¹China Coal Research Institute, Beijing, China.

|November 7, 2025

Summary

This summary is machine-generated.

This study introduces a new method for automatic lithology identification while drilling using acoustic pressure and rock physics parameters. This approach enhances reservoir prediction and automation in intelligent coal mine exploration.

More Related Videos

Data Processing Methods for 3D Seismic Imaging of Subsurface Volcanoes: Applications to the Tarim Flood Basalt

Data Processing Methods for 3D Seismic Imaging of Subsurface Volcanoes: Applications to the Tarim Flood Basalt

Published on: August 7, 2017

Pore-scale Imaging and Characterization of Hydrocarbon Reservoir Rock Wettability at Subsurface Conditions Using X-ray Microtomography

Pore-scale Imaging and Characterization of Hydrocarbon Reservoir Rock Wettability at Subsurface Conditions Using X-ray Microtomography

Published on: October 21, 2018

Related Experiment Videos

Last Updated: Jul 4, 2026

Reservoir Condition Pore-scale Imaging of Multiple Fluid Phases Using X-ray Microtomography

Reservoir Condition Pore-scale Imaging of Multiple Fluid Phases Using X-ray Microtomography

Published on: February 25, 2015

Data Processing Methods for 3D Seismic Imaging of Subsurface Volcanoes: Applications to the Tarim Flood Basalt

Data Processing Methods for 3D Seismic Imaging of Subsurface Volcanoes: Applications to the Tarim Flood Basalt

Published on: August 7, 2017

Pore-scale Imaging and Characterization of Hydrocarbon Reservoir Rock Wettability at Subsurface Conditions Using X-ray Microtomography

Pore-scale Imaging and Characterization of Hydrocarbon Reservoir Rock Wettability at Subsurface Conditions Using X-ray Microtomography

Published on: October 21, 2018

Area of Science:

Geology
Drilling Engineering
Data Science

Background:

Lithology identification during drilling is crucial for intelligent coal mine exploration.
Current methods lack accuracy and automation, hindering reservoir prediction.

Purpose of the Study:

To develop a novel method for automatic lithology identification while drilling.
To establish a mapping relationship between acoustic pressure and rock physics parameters.

Main Methods:

Collected core samples for rock specimen preparation (homogeneous and layered).
Designed and constructed a full-scale laboratory drilling system.
Developed a quantitative fitting model and an automatic identification algorithm based on acoustic pressure-rock physics parameter mapping.

Main Results:

Acoustic pressure is an effective feature for lithology identification.
The algorithm achieved varying recognition accuracies for different rock types (e.g., 71% for granite).
The method is robust to perforated transition zones.

Conclusions:

The proposed method offers a novel approach for real-time lithology identification during drilling.
This advancement is pivotal for intelligent coal mine exploration and automation.