Presentation is loading. Please wait.

Presentation is loading. Please wait.

Characterization of Youngstown Induced Seismicity Robert L. Walker Arman Khodabakhshnejad Mork Family Department of Chemical Engineering and Materials.

Similar presentations


Presentation on theme: "Characterization of Youngstown Induced Seismicity Robert L. Walker Arman Khodabakhshnejad Mork Family Department of Chemical Engineering and Materials."— Presentation transcript:

1 Characterization of Youngstown Induced Seismicity Robert L. Walker Arman Khodabakhshnejad Mork Family Department of Chemical Engineering and Materials Science Induced Seismicity Consortium

2 Outline  Background  Problem Statement  Correlation between Fluid Injection and Seismicity  Prior Work  Our Strategy  Conclusion

3 Event Background (Credit USGS,Youngstown 7½-minute quadrangle) (Credit Ohio Department of Natural Resources, 2012)

4 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)

5 Why is This Important? (From W. Y. Kim, 2008) (Credit Organization of American States) (Credit University of Arizona)

6 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)

7 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.

8 The Problem (Credit National Research Council) Unfortunately, seismometer networks may not be up to the task

9 Objective Development 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

10 Current Thinking Water/fluid pressure in fault = p For an to occur, the stress must exceed the critical shear stress on the fault: τ critical = c + ( σ n - p) Function of Hydraulic Stress only Majer, 2011

11 Working Hypothesis Mechanisms of Seismicity  Mechanical based seismicity  Lubrication based seismicity Youngstown Seismicity Over Time (Credit Ohio Department of Natural Resources, 2012) Water/fluid pressure in fault affects coefficient of friction µ τ critical = c + µ( σ n - p)

12 Correlations Between Fluid Injection and Seismicity (Majer, 2011, Relation after McGarr, 1976) (Ake et. al, 2005)

13 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 Injection data Pressure Injection Attributes Artificial Intelligence Qualitative & Quantitative Models Flow Rate Pressure Fluctuations Energy Analogy ANFIS Lubrication Model b – Value analysis from generated catalog PREDICTION

14 Northstar #1 Data

15 QC/Initial Testing: Surface Pressure Estimation

16 QC/Initial Testing: Energy Transfer Check After removing the high energy outlier…. Looks awful lonely, doesn’t it? Hm. Guess not. Suppose there’s more to it.

17 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.


Download ppt "Characterization of Youngstown Induced Seismicity Robert L. Walker Arman Khodabakhshnejad Mork Family Department of Chemical Engineering and Materials."

Similar presentations


Ads by Google