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What is Maptek DomainMCF?

Maptek DomainMCF utilizes cutting-edge machine learning techniques to define domain boundaries directly from sample data, streamlining the creation of resource models. Geologists can input data from drilling or sampling and obtain domain or grade models much faster than traditional resource modeling methods permit. This revolutionary tool eliminates the necessity for complex software typically found on desktop systems, allowing companies to shift costs from capital expenditures to operational budgets. With advanced cloud processing capabilities, users benefit from enhanced speed and security, while versatile licensing options cater to a range of user requirements. Resource models can be generated in a matter of minutes or hours, depending on variables such as deposit complexity, size, and data density. While conventional mining operations may only update their resource models a couple of times a year, DomainMCF allows for rapid modeling that competes with and often surpasses the results achieved via traditional approaches. You have complete authority over the modeling process, which removes the hassle of extensive preparatory work. Furthermore, the ability to quickly incorporate new data and refresh models ensures that resource evaluations remain accurate and up-to-date. This level of flexibility significantly transforms industries dependent on meticulous resource management, making it easier to adapt to changing circumstances in real-time. In essence, DomainMCF empowers geologists to make informed decisions with unprecedented speed and efficiency.

What is Kinemetrics PSD?

PSD is a specialized Windows application designed for the analysis of seismological data. It allows users to easily evaluate the quality of field-collected data, and it can process event (.EVT) files from various versions, including those up to 1.50. The software is specifically tailored to aid users in performing frequency analysis of seismic signals, requiring an EVT file as input to initiate several essential functions. One of its primary capabilities is calculating the Signal-to-Noise Ratio by taking the first 1024 data points as noise and the subsequent 1024 points after a trigger as the signal. Additionally, it calculates the Power Spectral Density using a one-sided auto spectral density function, offering users the ability to customize parameters such as corner filter, filter order, and the overlapping window. This level of adaptability not only enhances the user experience but also significantly improves the accuracy of data interpretation, allowing for a more comprehensive understanding of seismic events. Ultimately, PSD serves as a valuable tool for researchers and professionals in the field of seismology.

Media

Media

Integrations Supported

Maptek Vestrex

Integrations Supported

Maptek Vestrex

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Maptek

Date Founded

1981

Company Location

United States

Company Website

www.maptek.com/products/domainmcf/

Company Facts

Organization Name

Kinemetrics

Date Founded

1969

Company Location

United States

Company Website

kinemetrics.com/post_products/psd/

Categories and Features

Mining

3D Modeling
Cross Section Creation
Data Exchange
Data Storage
Exception Notification
Fence Diagrams
Log Map Creation
People Tracking
Pit Optimization Reporting
Risk Management
Volumetrics

Categories and Features

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