{"id":{"repo_id":"houston","oai_identifier":"oai:uh-ir.tdl.org:10657/17661"},"canonical_url":"https://search.dev.ndltd.org/etd/houston/oai:uh-ir.tdl.org:10657/17661","repository":{"repo_id":"houston","name":"University of Houston","base_url":"https://uh-ir.tdl.org/server/oai/request"},"display":{"title":"Force Chain Detection in Unconsolidated Sands","abstract":"Understanding the geomechanical properties of rocks is vital in petroleum engineering. The compressibility of a formation often correlates directly with the productivity of that reservoir. It is a common practice to extract core samples from reservoirs for the purposes of obtaining the reservoir properties and forecasting the reservoir productivity. Obtaining these properties is often met with many challenges. While it is very desirable to obtain properties such as porosity, permeability, and mineralogy, the behavior of the sample under different stress conditions is important to determine their change as the reservoir is depleted. The sample is rendered unusable for other measurements after the first test due to irrecoverable strains induced during the test. Since the core samples are limited in quantity and costly to obtain, the development of digital rock models comes into play as a solution. The ability to predict and simulate tests using a digitized version of the original state of the core sample is helpful in obtaining the rock properties since this process is nondestructive. In this work, the process of creating a digital rock model will address multiple obstacles when building the model. The first processing of the sample images involves removing random noise (salt and pepper) without impacting the structure of the sample (the grain edges). This has been accomplished by developing a denoising filter that accounts for the local environment and limiting the filtering near grain/pore boundaries. A customized program was also built to interactively allow the segmentation of the rock into pore space versus grain space. The initial application of the model will utilize discrete element modeling approach to simulate the force chain network of the sand pack and predict its behavior under further stress loading. The model will allow to extract the statistics and the distribution of the stress across the calculated volume and find the regions where the probability of higher stresses within the sand pack peaks and reaches a threshold that cause grain breakage.","abstract_html":"Understanding the geomechanical properties of rocks is vital in petroleum engineering. The compressibility of a formation often correlates directly with the productivity of that reservoir. It is a common practice to extract core samples from reservoirs for the purposes of obtaining the reservoir properties and forecasting the reservoir productivity. Obtaining these properties is often met with many challenges. While it is very desirable to obtain properties such as porosity, permeability, and mineralogy, the behavior of the sample under different stress conditions is important to determine their change as the reservoir is depleted. The sample is rendered unusable for other measurements after the first test due to irrecoverable strains induced during the test. Since the core samples are limited in quantity and costly to obtain, the development of digital rock models comes into play as a solution. The ability to predict and simulate tests using a digitized version of the original state of the core sample is helpful in obtaining the rock properties since this process is nondestructive. In this work, the process of creating a digital rock model will address multiple obstacles when building the model. The first processing of the sample images involves removing random noise (salt and pepper) without impacting the structure of the sample (the grain edges). This has been accomplished by developing a denoising filter that accounts for the local environment and limiting the filtering near grain/pore boundaries. A customized program was also built to interactively allow the segmentation of the rock into pore space versus grain space. The initial application of the model will utilize discrete element modeling approach to simulate the force chain network of the sand pack and predict its behavior under further stress loading. The model will allow to extract the statistics and the distribution of the stress across the calculated volume and find the regions where the probability of higher stresses within the sand pack peaks and reaches a threshold that cause grain breakage.","abstract_has_math":false,"creators":["Al-Gobi, Ghaleb A."],"institution":"University of Houston","degree_name":"Master of Science","degree_level":"Masters","degree_discipline":"Petroleum Engineering","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":["Myers, Michael T","Hathon, Lori A","Soliman, Mohamed Y"],"year":2024,"date_issued":"2024-05-07","date_published":"2024-05-07","updated_at":"2026-07-24T02:32:12Z","subjects":["Force chains","unconsolidated sands","sand pack","granular pack","stress distribution","stress statistics","digital rock model","image processing","noise reduction","micro-CT"],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/10657/17661","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Myers, Michael T","Hathon, Lori A","Soliman, Mohamed Y"]},{"key":"dc:creator","label":"Author","values":["Al-Gobi, Ghaleb A."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2024-07-26T03:52:55Z"]},{"key":"dc:date.issued","label":"Date","values":["2024-05-07"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Petroleum Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Houston"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Force chains","unconsolidated sands","sand pack","granular pack","stress distribution","stress statistics","digital rock model","image processing","noise reduction","micro-CT"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://hdl.handle.net/10657/17661"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Understanding the geomechanical properties of rocks is vital in petroleum engineering. The compressibility of a formation often correlates directly with the productivity of that reservoir. It is a common practice to extract core samples from reservoirs for the purposes of obtaining the reservoir properties and forecasting the reservoir productivity. Obtaining these properties is often met with many challenges. While it is very desirable to obtain properties such as porosity, permeability, and mineralogy, the behavior of the sample under different stress conditions is important to determine their change as the reservoir is depleted. The sample is rendered unusable for other measurements after the first test due to irrecoverable strains induced during the test. Since the core samples are limited in quantity and costly to obtain, the development of digital rock models comes into play as a solution. The ability to predict and simulate tests using a digitized version of the original state of the core sample is helpful in obtaining the rock properties since this process is nondestructive. In this work, the process of creating a digital rock model will address multiple obstacles when building the model. The first processing of the sample images involves removing random noise (salt and pepper) without impacting the structure of the sample (the grain edges). This has been accomplished by developing a denoising filter that accounts for the local environment and limiting the filtering near grain/pore boundaries. A customized program was also built to interactively allow the segmentation of the rock into pore space versus grain space. The initial application of the model will utilize discrete element modeling approach to simulate the force chain network of the sand pack and predict its behavior under further stress loading. The model will allow to extract the statistics and the distribution of the stress across the calculated volume and find the regions where the probability of higher stresses within the sand pack peaks and reaches a threshold that cause grain breakage."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Force Chain Detection in Unconsolidated Sands"]}]}],"canonical_facts":{"dc:contributor.committeemember":["Myers, Michael T","Hathon, Lori A","Soliman, Mohamed Y"],"dc:creator":["Al-Gobi, Ghaleb A."],"dc:date.accessioned":["2024-07-26T03:52:55Z"],"dc:date.issued":["2024-05-07"],"dc:description.abstract":["Understanding the geomechanical properties of rocks is vital in petroleum engineering. The compressibility of a formation often correlates directly with the productivity of that reservoir. It is a common practice to extract core samples from reservoirs for the purposes of obtaining the reservoir properties and forecasting the reservoir productivity. Obtaining these properties is often met with many challenges. While it is very desirable to obtain properties such as porosity, permeability, and mineralogy, the behavior of the sample under different stress conditions is important to determine their change as the reservoir is depleted. The sample is rendered unusable for other measurements after the first test due to irrecoverable strains induced during the test. Since the core samples are limited in quantity and costly to obtain, the development of digital rock models comes into play as a solution. The ability to predict and simulate tests using a digitized version of the original state of the core sample is helpful in obtaining the rock properties since this process is nondestructive. In this work, the process of creating a digital rock model will address multiple obstacles when building the model. The first processing of the sample images involves removing random noise (salt and pepper) without impacting the structure of the sample (the grain edges). This has been accomplished by developing a denoising filter that accounts for the local environment and limiting the filtering near grain/pore boundaries. A customized program was also built to interactively allow the segmentation of the rock into pore space versus grain space. The initial application of the model will utilize discrete element modeling approach to simulate the force chain network of the sand pack and predict its behavior under further stress loading. The model will allow to extract the statistics and the distribution of the stress across the calculated volume and find the regions where the probability of higher stresses within the sand pack peaks and reaches a threshold that cause grain breakage."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["https://hdl.handle.net/10657/17661"],"dc:language.iso":["en"],"dc:subject":["Force chains","unconsolidated sands","sand pack","granular pack","stress distribution","stress statistics","digital rock model","image processing","noise reduction","micro-CT"],"dc:title":["Force Chain Detection in Unconsolidated Sands"],"dc:type":["Thesis"],"thesis:degree_discipline":["Petroleum Engineering"],"thesis:degree_level":["Masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["University of Houston"]},"updated_at":"2026-07-24T02:32:12Z"}