{"id":23,"date":"2015-07-10T17:12:09","date_gmt":"2015-07-10T17:12:09","guid":{"rendered":"http:\/\/sites.warnercnr.colostate.edu\/lisastright\/?page_id=23"},"modified":"2015-07-10T19:38:04","modified_gmt":"2015-07-10T19:38:04","slug":"research-areas","status":"publish","type":"page","link":"https:\/\/sites.warnercnr.colostate.edu\/lisastright\/research-areas\/","title":{"rendered":"Research Areas"},"content":{"rendered":"<div class=\"wpb-content-wrapper\"><p>[vc_row][vc_column width=&#8221;1\/1&#8243;][vc_column_text css_animation=&#8221;&#8221;]<\/p>\n<h1>Research Areas<\/h1>\n<p><strong>1) Outcrop modeling studies\u00a0<\/strong><\/p>\n<p><strong><em>Quantifying outcrop interpretation uncertainty\u00a0<\/em><\/strong><\/p>\n<p>3D interpretations of outcropping sediments are inhibited by loss of section through erosion or\u00a0by partial outcrop exposures. \u00a0This part of my research focuses on translating measured and\u00a0interpreted outcrop data into 3D models. \u00a0The purpose is to model spatial uncertainty due to limited\u00a0exposures and to validate interpretations by 3D spatial modeling. \u00a0Furthermore, modeling can be used to test interpretations and hypothesis.<\/p>\n<p><strong><em>Utilizing outcrop analogs to build predictive subsurface models\u00a0<\/em><\/strong><\/p>\n<p>With the introduction and adaptation of multiple-point geostatistics and event-based modeling, more geologic expertise can be\u00a0included in geostatistical models. I am studying how we can directly transfer information and knowledge acquired from 3D outcrop modeling studies to build better subsurface geomodels\u00a0for reservoir performance prediction.<\/p>\n<p><strong>2) Seismic reservoir characterization\u00a0<\/strong><\/p>\n<p>I have developed a multi-scale, multi-attribute well-to-seismic calibration that facilitates subseismic scale interpretation of seismic attributes within a probabilistic framework. \u00a0This methodology\u00a0leverages bed-scale information directly from wellbore data or indirectly from analog data, calibrates\u00a0this information to seismic attributes and produces a prediction of the probability of seismic pixel\u00a0containing a sub-seismic scale pattern. \u00a0For example, a search of \u201cWhat is the probability of\u00a0encountering an average sandstone bed thickness greater than 1 meter given my seismic attributes\u00a0and analog lithofacies patterns?\u201d would yield a 3D probability cube revealing locations where\u00a0one is likely to encounter this condition.<\/p>\n<p><strong>3) Reservoir characterization to appraise reservoir connectivity<\/strong><\/p>\n<p>This research focuses on the critical link between geologic heterogeneity and reservoir connectivity. \u00a0I focus on generating methods to translate the multiple scales of reservoir heterogeneity in geomodels to make more reliable recovery predictions and development scenarios. \u00a0Studies investigate both static and dynamic measures of connectivity, and emphasize 3D connectivity.[\/vc_column_text][\/vc_column][\/vc_row]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>[vc_row][vc_column width=&#8221;1\/1&#8243;][vc_column_text css_animation=&#8221;&#8221;] Research Areas 1) Outcrop modeling studies\u00a0 Quantifying outcrop interpretation uncertainty\u00a0 3D interpretations of outcropping sediments are inhibited by loss of section through erosion or\u00a0by partial outcrop exposures. \u00a0This part of my research focuses on translating measured and\u00a0interpreted &hellip; <a href=\"https:\/\/sites.warnercnr.colostate.edu\/lisastright\/research-areas\/\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":44,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-23","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sites.warnercnr.colostate.edu\/lisastright\/wp-json\/wp\/v2\/pages\/23","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.warnercnr.colostate.edu\/lisastright\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.warnercnr.colostate.edu\/lisastright\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.warnercnr.colostate.edu\/lisastright\/wp-json\/wp\/v2\/users\/44"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.warnercnr.colostate.edu\/lisastright\/wp-json\/wp\/v2\/comments?post=23"}],"version-history":[{"count":6,"href":"https:\/\/sites.warnercnr.colostate.edu\/lisastright\/wp-json\/wp\/v2\/pages\/23\/revisions"}],"predecessor-version":[{"id":59,"href":"https:\/\/sites.warnercnr.colostate.edu\/lisastright\/wp-json\/wp\/v2\/pages\/23\/revisions\/59"}],"wp:attachment":[{"href":"https:\/\/sites.warnercnr.colostate.edu\/lisastright\/wp-json\/wp\/v2\/media?parent=23"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}