Application of Causal Inference to Analyze Microseismic and Seismic Events in Unconventional Plays

This research applies advanced causal inference techniques to uncover intricate causal relationships in two domains within the oil and gas industry - microseismic events and induced seismicity. Microseismic events are small-magnitude seismic events that occur due to crack propagation and rock failur...

Full description

Bibliographic Details
Main Author: Rojas Conde, Oliver
Other Authors: Misra, Siddharth, Blasingame, Thomas, Chakrabortty, Abhishek
Format: Thesis
Language:English
Published: 2024
Subjects:
DML
Online Access:https://hdl.handle.net/1969.1/202886
id fttexasamuniv:oai:oaktrust.library.tamu.edu:1969.1/202886
record_format openpolar
spelling fttexasamuniv:oai:oaktrust.library.tamu.edu:1969.1/202886 2024-09-15T18:03:51+00:00 Application of Causal Inference to Analyze Microseismic and Seismic Events in Unconventional Plays Rojas Conde, Oliver Misra, Siddharth Blasingame, Thomas Chakrabortty, Abhishek 2024-07-30T22:44:47Z application/pdf https://hdl.handle.net/1969.1/202886 en eng https://hdl.handle.net/1969.1/202886 Causal inference Microseismic events Induced seismicity Hydraulic fracturing Thesis text 2024 fttexasamuniv 2024-07-31T14:05:20Z This research applies advanced causal inference techniques to uncover intricate causal relationships in two domains within the oil and gas industry - microseismic events and induced seismicity. Microseismic events are small-magnitude seismic events that occur due to crack propagation and rock failure caused by hydraulic fracturing operations. In contrast, induced seismicity refers to larger magnitude earthquakes that occur later in time and over a more extensive area due to subsurface fluid injection operations such as wastewater disposal or hydraulic fracturing. Regarding microseismic events, the study utilizes data from two horizontal wells, MIP 5H and MIP 3H, situated within the Marcellus Shale Energy and Environment Laboratory (MSEEL). Through meticulous spatiotemporal sampling and the formulation of treatment, outcome and confounder variables, Double Machine Learning (DML) is implemented to estimate causal effects. The findings reveal pivotal causal mechanisms governing the characteristics of new microseismic events based on attributes of prior proximal events. High-magnitude prior events are linked to subsequent high-magnitude and delayed new events. Spatial and temporal concentration of prior events also causally impact new event proximity and timing. Appropriate confounder selection is critical, as errors may lead to over/underestimations of the Average Treatment Effect (ATE) by up to 156%. For induced seismicity, the research explores the causal relationship between injection activities and earthquakes in Oklahoma state using well and seismic data over a 7-year period. Spatiotemporal sampling facilitates the analysis of various grid-time combinations. DML results indicate that approximately 100 water disposal wells induce about 53 earthquakes over 4400 km2 within 54 to 58 days, while 100 hydraulic fracturing wells lead to 36 earthquakes within 16 to 324 km2 over 102 to 110 days. This reveals a more rapid and expansive impact of water disposal versus hydraulic fracturing on induced seismicity. However, ... Thesis DML Texas A&M University Digital Repository
institution Open Polar
collection Texas A&M University Digital Repository
op_collection_id fttexasamuniv
language English
topic Causal inference
Microseismic events
Induced seismicity
Hydraulic fracturing
spellingShingle Causal inference
Microseismic events
Induced seismicity
Hydraulic fracturing
Rojas Conde, Oliver
Application of Causal Inference to Analyze Microseismic and Seismic Events in Unconventional Plays
topic_facet Causal inference
Microseismic events
Induced seismicity
Hydraulic fracturing
description This research applies advanced causal inference techniques to uncover intricate causal relationships in two domains within the oil and gas industry - microseismic events and induced seismicity. Microseismic events are small-magnitude seismic events that occur due to crack propagation and rock failure caused by hydraulic fracturing operations. In contrast, induced seismicity refers to larger magnitude earthquakes that occur later in time and over a more extensive area due to subsurface fluid injection operations such as wastewater disposal or hydraulic fracturing. Regarding microseismic events, the study utilizes data from two horizontal wells, MIP 5H and MIP 3H, situated within the Marcellus Shale Energy and Environment Laboratory (MSEEL). Through meticulous spatiotemporal sampling and the formulation of treatment, outcome and confounder variables, Double Machine Learning (DML) is implemented to estimate causal effects. The findings reveal pivotal causal mechanisms governing the characteristics of new microseismic events based on attributes of prior proximal events. High-magnitude prior events are linked to subsequent high-magnitude and delayed new events. Spatial and temporal concentration of prior events also causally impact new event proximity and timing. Appropriate confounder selection is critical, as errors may lead to over/underestimations of the Average Treatment Effect (ATE) by up to 156%. For induced seismicity, the research explores the causal relationship between injection activities and earthquakes in Oklahoma state using well and seismic data over a 7-year period. Spatiotemporal sampling facilitates the analysis of various grid-time combinations. DML results indicate that approximately 100 water disposal wells induce about 53 earthquakes over 4400 km2 within 54 to 58 days, while 100 hydraulic fracturing wells lead to 36 earthquakes within 16 to 324 km2 over 102 to 110 days. This reveals a more rapid and expansive impact of water disposal versus hydraulic fracturing on induced seismicity. However, ...
author2 Misra, Siddharth
Blasingame, Thomas
Chakrabortty, Abhishek
format Thesis
author Rojas Conde, Oliver
author_facet Rojas Conde, Oliver
author_sort Rojas Conde, Oliver
title Application of Causal Inference to Analyze Microseismic and Seismic Events in Unconventional Plays
title_short Application of Causal Inference to Analyze Microseismic and Seismic Events in Unconventional Plays
title_full Application of Causal Inference to Analyze Microseismic and Seismic Events in Unconventional Plays
title_fullStr Application of Causal Inference to Analyze Microseismic and Seismic Events in Unconventional Plays
title_full_unstemmed Application of Causal Inference to Analyze Microseismic and Seismic Events in Unconventional Plays
title_sort application of causal inference to analyze microseismic and seismic events in unconventional plays
publishDate 2024
url https://hdl.handle.net/1969.1/202886
genre DML
genre_facet DML
op_relation https://hdl.handle.net/1969.1/202886
_version_ 1810441304558010368