Earthquake b-value calculator (Gutenberg-Richter)

Load a CSV or TSV catalog, build the cumulative frequency-magnitude distribution, and estimate b and a values.

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Catalog input

Ready
Example workflow: load a sample catalog, set the completeness magnitude Mc, then read the b-value with N above Mc and its uncertainty. A higher b-value means smaller events make up a larger share of the catalog; a lower b-value means larger events are relatively more common.
Number of rows read
After analysis
Number of valid events
After analysis
Number of events after filtering
After analysis
Events at or above Mc (N)
After analysis
Detected columns
After analysis

Filter (optional)

Estimation settings

Estimation method

Results

b value
Awaiting analysis
Method appears after analysis.
a value
Awaiting analysis
N appears after analysis.
95% confidence interval (b)
Awaiting analysis
CI details appear after analysis.

Cumulative FMD graph

Awaiting analysis

Run an analysis to display the graph.

FMD (Frequency-Magnitude Distribution)

M Events Cumulative (M or greater) log10(cumulative)
Run an analysis to display FMD rows.

Assumptions and limits

FAQ

What does a large or small b value mean?

A higher b-value means smaller earthquakes make up a larger share of the catalog. Interpretation still depends on data quality and Mc.

How should I choose Mc?

Catalog completeness changes with region, period, and observation network. This calculator does not estimate Mc automatically, so set it from your catalog, literature, or analysis purpose.

Can I use these results for prediction?

Use the results as exploratory evidence only. They are not enough on their own for earthquake forecasts or disaster-response decisions.

What catalog data should I enter first?

Start with earthquake magnitudes from a consistent catalog and set the completeness magnitude Mc before estimating b. Exclude mixed regions or time periods unless you intentionally want a combined sample.

Why can b-value estimates differ between tools?

Different tools may use different Mc choices, magnitude bins, maximum-likelihood formulas, uncertainty estimates, or catalog filters. Align those assumptions before comparing b values.

Earthquake b-value analysis notes

Completeness magnitude matters

The b value is sensitive to Mc. If small events are missing from the catalog, the slope can be biased and the uncertainty will look more precise than it should.

Keep the catalog consistent

Use one region, time window, magnitude scale, and detection network when possible. Mixing catalogs can change the magnitude distribution before the calculation even starts.

Read b with uncertainty

A higher b value generally means relatively more small events; a lower value means relatively more large events. Check uncertainty and sample size before interpreting the difference.

Common mistakes

Do not use aftershock clusters, changing network coverage, or arbitrary Mc values without noting the limitation. Do not compare rounded b values without checking the inputs.

Use limitations

This page supports exploratory Gutenberg-Richter analysis. It does not forecast earthquakes or replace a seismological hazard assessment.