{"id":{"repo_id":"houston","oai_identifier":"oai:uh-ir.tdl.org:10657/2925"},"canonical_url":"https://search.dev.ndltd.org/etd/houston/oai:uh-ir.tdl.org:10657/2925","repository":{"repo_id":"houston","name":"University of Houston","base_url":"https://uh-ir.tdl.org/server/oai/request"},"display":{"title":"Scaling and Correlation Functions to Map and Understand the Heterogeneity of the Productive Layer","abstract":"One of the most challenging problems in the development stage of a field is the prediction of the fluid type as well as lateral and vertical heterogeneities in the reservoir away from the well-location. This multi-scale approach, both downscaling and upscaling to the solution is a two-step process based on the Pair Correlation Function (PCF) approximation method that takes into account the effect of scattering by considering the interactions between any two points of a heterogeneous medium. The amplitude of the correlations of fluctuations are estimated for various combinations of measured and calculated physical properties like velocity, density, porosity, and elastic stiffness tensors. The fluctuations will be higher if the medium is heterogeneous due to sudden changes in lithology or if the properties of the inclusions are drastically different from the matrix, as in the case of a productive layer and so we expect higher values for amplitude. The first step is to detect the heterogeneous layer from the well-logs for a range of frequencies. Hermite Distributed Approximating Functionals (HDAFs) and Simple Moving Average (SMA) are used as the averaging or upscaling methods for calculating the amplitude of the fluctuations. The results show that to detect the productive layers at lower frequencies that corresponds to seismic data, HDAF gives better results. The second step is downscaling where logs are predicted from the seismic data using scaled functions, which are then used to identify and map the heterogeneous layer and predict future well locations. This methodology is also applied to study the heterogeneity in a meandering fluvial channel fill using well–logs in the clastic Tertiary sediments of northern part of South Marsh Island in the Gulf of Mexico (GoM).","abstract_html":"One of the most challenging problems in the development stage of a field is the prediction of the fluid type as well as lateral and vertical heterogeneities in the reservoir away from the well-location. This multi-scale approach, both downscaling and upscaling to the solution is a two-step process based on the Pair Correlation Function (PCF) approximation method that takes into account the effect of scattering by considering the interactions between any two points of a heterogeneous medium. The amplitude of the correlations of fluctuations are estimated for various combinations of measured and calculated physical properties like velocity, density, porosity, and elastic stiffness tensors. The fluctuations will be higher if the medium is heterogeneous due to sudden changes in lithology or if the properties of the inclusions are drastically different from the matrix, as in the case of a productive layer and so we expect higher values for amplitude. The first step is to detect the heterogeneous layer from the well-logs for a range of frequencies. Hermite Distributed Approximating Functionals (HDAFs) and Simple Moving Average (SMA) are used as the averaging or upscaling methods for calculating the amplitude of the fluctuations. The results show that to detect the productive layers at lower frequencies that corresponds to seismic data, HDAF gives better results. The second step is downscaling where logs are predicted from the seismic data using scaled functions, which are then used to identify and map the heterogeneous layer and predict future well locations. This methodology is also applied to study the heterogeneity in a meandering fluvial channel fill using well–logs in the clastic Tertiary sediments of northern part of South Marsh Island in the Gulf of Mexico (GoM).","abstract_has_math":false,"creators":["Ravindranathan, Ramya 1981-"],"institution":"University of Houston","degree_name":"Doctor of Philosophy","degree_level":"Doctoral","degree_discipline":"Geophysics","degree_department":null,"school":null,"contributors":[],"advisors":["Chesnokov, Evgeni M."],"committee_chairs":[],"committee_members":["Zheng, Yingcai","Dupré, William R.","Kouri, Donald J."],"year":2017,"date_issued":"2017-12","date_published":"2017-12","updated_at":"2026-07-24T02:33:06Z","subjects":["Downscaling","Seismic","Pair-correlation function","Rock physics","Well logs"],"languages":["eng"],"rights":["The author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s)."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10657/2925","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Chesnokov, Evgeni M."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Zheng, Yingcai","Dupré, William R.","Kouri, Donald J."]},{"key":"dc:creator","label":"Author","values":["Ravindranathan, Ramya 1981-"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2018-03-12T20:11:32Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2018-03-12T20:11:32Z"]},{"key":"dc:date.issued","label":"Date","values":["2017-12"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Geophysics"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]},{"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":["Downscaling","Seismic","Pair-correlation function","Rock physics","Well logs"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["The author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s)."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10657/2925"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["One of the most challenging problems in the development stage of a field is the prediction of the fluid type as well as lateral and vertical heterogeneities in the reservoir away from the well-location. This multi-scale approach, both downscaling and upscaling to the solution is a two-step process based on the Pair Correlation Function (PCF) approximation method that takes into account the effect of scattering by considering the interactions between any two points of a heterogeneous medium. The amplitude of the correlations of fluctuations are estimated for various combinations of measured and calculated physical properties like velocity, density, porosity, and elastic stiffness tensors. The fluctuations will be higher if the medium is heterogeneous due to sudden changes in lithology or if the properties of the inclusions are drastically different from the matrix, as in the case of a productive layer and so we expect higher values for amplitude. The first step is to detect the heterogeneous layer from the well-logs for a range of frequencies. Hermite Distributed Approximating Functionals (HDAFs) and Simple Moving Average (SMA) are used as the averaging or upscaling methods for calculating the amplitude of the fluctuations. The results show that to detect the productive layers at lower frequencies that corresponds to seismic data, HDAF gives better results. The second step is downscaling where logs are predicted from the seismic data using scaled functions, which are then used to identify and map the heterogeneous layer and predict future well locations. This methodology is also applied to study the heterogeneity in a meandering fluvial channel fill using well–logs in the clastic Tertiary sediments of northern part of South Marsh Island in the Gulf of Mexico (GoM)."]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Scaling and Correlation Functions to Map and Understand the Heterogeneity of the Productive Layer"]}]}],"canonical_facts":{"dc:contributor.advisor":["Chesnokov, Evgeni M."],"dc:contributor.committeemember":["Zheng, Yingcai","Dupré, William R.","Kouri, Donald J."],"dc:creator":["Ravindranathan, Ramya 1981-"],"dc:date.accessioned":["2018-03-12T20:11:32Z"],"dc:date.available":["2018-03-12T20:11:32Z"],"dc:date.issued":["2017-12"],"dc:description.abstract":["One of the most challenging problems in the development stage of a field is the prediction of the fluid type as well as lateral and vertical heterogeneities in the reservoir away from the well-location. This multi-scale approach, both downscaling and upscaling to the solution is a two-step process based on the Pair Correlation Function (PCF) approximation method that takes into account the effect of scattering by considering the interactions between any two points of a heterogeneous medium. The amplitude of the correlations of fluctuations are estimated for various combinations of measured and calculated physical properties like velocity, density, porosity, and elastic stiffness tensors. The fluctuations will be higher if the medium is heterogeneous due to sudden changes in lithology or if the properties of the inclusions are drastically different from the matrix, as in the case of a productive layer and so we expect higher values for amplitude. The first step is to detect the heterogeneous layer from the well-logs for a range of frequencies. Hermite Distributed Approximating Functionals (HDAFs) and Simple Moving Average (SMA) are used as the averaging or upscaling methods for calculating the amplitude of the fluctuations. The results show that to detect the productive layers at lower frequencies that corresponds to seismic data, HDAF gives better results. The second step is downscaling where logs are predicted from the seismic data using scaled functions, which are then used to identify and map the heterogeneous layer and predict future well locations. This methodology is also applied to study the heterogeneity in a meandering fluvial channel fill using well–logs in the clastic Tertiary sediments of northern part of South Marsh Island in the Gulf of Mexico (GoM)."],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["http://hdl.handle.net/10657/2925"],"dc:language.iso":["eng"],"dc:rights":["The author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s)."],"dc:subject":["Downscaling","Seismic","Pair-correlation function","Rock physics","Well logs"],"dc:title":["Scaling and Correlation Functions to Map and Understand the Heterogeneity of the Productive Layer"],"thesis:degree_discipline":["Geophysics"],"thesis:degree_level":["Doctoral"],"thesis:degree_name":["Doctor of Philosophy"],"thesis:institution_name":["University of Houston"]},"updated_at":"2026-07-24T02:33:06Z"}