Characterization of Youngstown Induced Seismicity

Robert L. WalkerArman Khodabakhshnejad

Mork Family Department of Chemical Engineering and Materials ScienceInduced Seismicity Consortium

Outline

Background

Problem Statement

Correlation between Fluid Injection and Seismicity

Prior Work

Our Strategy

Conclusion

Event Background

(Credit USGS ,Youngstown 7½-minute quadrangle)

(Credit Ohio Department of Natural Resources, 2012)

Potential Examples of Induced Seismicity

(From Seeber et. al, 2004)

(From Nicholson et. Al, 1988)

1986?

In Northeast Ohio….

1987 & 2001?

In the Continental US….

(Credit National Research Council, 2012)

Why is This Important?

(From W. Y. Kim, 2008)

(Credit Organization of

American States)

(Credit University of

Arizona)

So You Want to Cause an Earthquake….

The time tested approach: Literature has suggested that Seismic

Tremors can also be generated from….• Mining• Other Earthquakes• Geothermal Energy Generation• Dams• Hydrocarbon Reservoir Depletion• Reservoir Changes [i.e. Lake]• Nuclear Tests• Skyscraper Construction [Taipei 101]• Hydraulic Fracturing• Wastewater Disposal• Rainfall and Snowmelt (one study, at least)

Mitigation: Spotlight on Ohio

• It is thought that larger (M3-4) events are preceded by micro-earthquakes

• Key to anticipating [and hopefully avoiding] larger events is a sensitive, robust seismometer network • Ohio has ~180

Class II injection wells, now classified as either “shallow” or “deep,” respective to a 7000 foot reference depth.

• Effective Oct. 2012, all “deep” wells are required to submit a seismic monitoring plan, or if possible create their own seismic network.

The Problem

(Credit National Research Council)

Unfortunately, seismometer networks may not be up to the task

ObjectiveDevelopment of a model that can detect an

increased likelihood of Induced Seismic events

(From M.D. Zoback, 2012)

This model will take inspiration from previous correlations, as well as the proposed “Traffic Light Model” of M. D. Zoback

Current Thinking

Water/fluid pressurein fault = p

• For an to occur, the stress must exceed the critical shear stress on the fault: τcritical = c + (σn - p)

• Function of Hydraulic Stress only

Majer, 2011

Working Hypothesis

Mechanisms of Seismicity

Mechanical based seismicity

Lubrication based seismicity

50 100 150 200 250 300 350 4000

0.5

1

1.5

2

2.5

33.5

4

4.5

Day

Mom

ent

Mag

nitu

de

Youngstown Seismicity Over Time

(Credit Ohio Department of Natural Resources, 2012)

Water/fluid pressurein fault affects coefficient of friction µτ critical = c + µ(σn - p)

Correlations Between Fluid Injection and Seismicity

(Majer, 2011, Relation after McGarr, 1976)

(Ake et. al, 2005)

Probabilistic Model

Model Development Flowchart

B Value Analysis

Nearby Seismic Events

∑ Energy Transfer

Corrected Pressure

Data

Data Analysis has yielded attributes related to seismic

activity

Adaptive NeuroFuzzy Inference System will

be employed to predict seismic events

Physically derived model will test

predictive model

Generated Catalog

from Gathered

Data Past Seismic Records

0 100 200 300 400012345

Injection data

Pressure

Injection Attributes

Artificial Intelligence

Qualitative & Quantitative

Models

Flow Rate

Pressure Fluctuation

s

Energy

Analogy

ANFIS

Lubrication Model

b – Value analysis from

generated catalog

PREDICTION

Northstar #1 Data

0 50 100 150 200 250 300 3500

0.2

0.4

0.6

0.8

1

1.2

Normalized Cumulative Injection Normalized Total Energy Release

Day

Normalize

d

QC/Initial Testing: Surface Pressure Estimation

QC/Initial Testing: Energy Transfer Check

After removing the high energy outlier….

𝐸𝑡𝑟𝑎𝑛𝑠𝑓𝑒𝑟𝑒𝑑=𝑃𝑟𝑒𝑠𝑠𝑢𝑟𝑒×𝑉𝑜𝑙𝑢𝑚𝑒

Looks awful lonely, doesn’t it?

Hm. Guess not. Suppose there’s more to it.

Conclusion

- Based upon initial analysis of available data, a pattern of seismicity can be identified.

- Cumulative fluid injection, injection pressure, and past seismic events can serve as fundamental components of a predictive model.

- We believe that the “dual mechanism” source of seismicity may be able to explain certain patterns of seismicity and perhaps large seismic events.

- If so, this pattern could as a basis for a predictive model.