{"id":14570,"date":"2022-09-16T10:54:27","date_gmt":"2022-09-16T09:54:27","guid":{"rendered":"https:\/\/www.westwoodenergy.com\/?p=14570"},"modified":"2025-03-17T16:39:44","modified_gmt":"2025-03-17T16:39:44","slug":"prospect-risk-and-benchmarking-using-wildcat","status":"publish","type":"post","link":"https:\/\/www.westwoodenergy.com\/reports\/prospect-risk-and-benchmarking-using-wildcat","title":{"rendered":"Prospect Risk and Benchmarking using Wildcat"},"content":{"rendered":"[vc_row type=”in_container” full_screen_row_position=”middle” column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” scene_position=”center” text_color=”dark” text_align=”left” row_border_radius=”none” row_border_radius_applies=”bg” overflow=”visible” overlay_strength=”0.3″ gradient_direction=”left_to_right” shape_divider_position=”bottom” bg_image_animation=”none”][vc_column column_padding=”no-extra-padding” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_direction_desktop=”default” column_element_spacing=”default” desktop_text_alignment=”default” tablet_text_alignment=”default” phone_text_alignment=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_backdrop_filter=”none” column_shadow=”none” column_border_radius=”none” column_link_target=”_self” column_position=”default” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/1″ tablet_width_inherit=”default” animation_type=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid”][tabbed_section style=”default” tab_change_animation=”fade” alignment=”left” spacing=”default” tab_color=”Accent-Color” vs_content_animation=”fade” vs_link_animation=”opacity” vs_navigation_alignment=”left” vs_navigation_width_2=”25%” vs_navigation_func=”default” vs_navigation_width=”regular” vs_navigation_spacing=”15px” vs_navigation_mobile_display=”visible” vs_tab_spacing=”5%”][tab icon_family=”none” title=”Report Summary” id=”1742229572736-4″ tab_id=”1742229572737-1″][vc_column_text]\n

Report Summary<\/h2>\n

The Industry has a long track record of generally underestimating the chance of geological success of
\nexploration prospects and an overestimation of success case volumes, resulting in a significant
\nproportion of non-commercial discoveries. This is well documented in the literature and supported by
\ndata from Westwood\u2019s Wildcat database and information shared in Rose & Associates Risk
\nCoordinators network.
\nWestwood\u2019s Wildcat database includes 220 technical or commercial discoveries made since 2008
\nwhere both pre- and post drill resource estimates are available. These data demonstrate that 78% of
\ndiscoveries have found less than the pre-drill P50 estimate and 28% have been lower than the pre-drill
\nP90 (assuming that reported pre-drill volumes represent the P50 case). 45% of frontier discoveries
\nhave found less than the pre-drill P90 estimate. Reported P10\/P90 ratios vary between 1.5 and 41.5
\nwith an average of 8.3.<\/p>\n

Best practice advocates the use of regular \u201clook back analyses\u201d to understand where systematic errors
\nin estimation of chance of success or success case volumes may be generated. Look back analyses,
\nhowever, require access to a statistically significant number of wells. This can be difficult for
\ncompanies with limited exploration programmes and has become exacerbated by the reduction in
\nglobal exploration activity following the oil price crash of 2014.<\/p>\n

Exploration success rates and discovered volumes typically vary according to the maturity of a play
\nbeing explored, with success rates typically increasing and volumes decreasing as a play moves along
\nthe creaming curve. \u201cBase rate\u201d success rates and volumes can provide a benchmark to guide prospect
\nchance of success and volume estimation whilst not replacing effective technical assurance of
\nexploration activity.<\/p>\n

Access to global prospect analogue databases can provide effective calibration and benchmarking of
\nvolumes ranges and expected success rates by allowing plays to be compared to local or global
\nanalogues taking into account geology and play maturity. The use of play analogue databases can also
\nmitigate against the cognitive bias that often leads to inaccurate estimation of risk and volume.[\/vc_column_text][\/tab][tab icon_family=”none” title=”Report Contents” id=”1742229572760-3″ tab_id=”1742229572760-7″][vc_column_text]\n

    \n
  1. Summary <\/strong><\/li>\n
  2. Introduction<\/strong><\/li>\n
  3. Estimation of Chance of Success<\/strong>\n
      \n
    • Examples from Literature<\/li>\n<\/ul>\n<\/li>\n
    • Estimation of Success Case Volumes<\/strong>\n
        \n
      • Examples from Literature<\/li>\n
      • Examples from Wildcat\n
          \n
        • Prospect Size<\/li>\n
        • Play Maturity<\/li>\n
        • Trap Type<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n
        • Using Wildcat to Calibrate Chance of Success<\/strong><\/li>\n
        • Using Wildcat to Calibrate Success Case Volumes<\/strong>\n
            \n
          • Example: Gulf of Mexico<\/li>\n
          • Example: Barents Sea<\/li>\n<\/ul>\n<\/li>\n
          • Discussion<\/strong>\n
              \n
            • Current Best Practice in Risk and Resource Estimation<\/li>\n
            • The Importance of Lookback Analysis<\/li>\n
            • Impact of Cognitive Bias<\/li>\n
            • The Value of Global Databases<\/li>\n<\/ul>\n<\/li>\n
            • Conclusions<\/strong><\/li>\n
            • References <\/strong><\/li>\n
            • Disclaimer<\/strong><\/li>\n<\/ol>\n[\/vc_column_text][\/tab][\/tabbed_section][\/vc_column][\/vc_row][vc_row type=”in_container” full_screen_row_position=”middle” column_margin=”default” column_direction=”default” column_direction_tablet=”default” column_direction_phone=”default” bg_color=”#2c293e” scene_position=”center” text_color=”dark” text_align=”left” row_border_radius=”none” row_border_radius_applies=”bg” overflow=”visible” overlay_strength=”0.3″ gradient_direction=”left_to_right” shape_divider_position=”bottom” bg_image_animation=”none” gradient_type=”default” shape_type=””][vc_column column_padding=”padding-3-percent” column_padding_tablet=”inherit” column_padding_phone=”inherit” column_padding_position=”all” column_element_direction_desktop=”default” column_element_spacing=”default” desktop_text_alignment=”default” tablet_text_alignment=”default” phone_text_alignment=”default” background_color_opacity=”1″ background_hover_color_opacity=”1″ column_backdrop_filter=”none” column_shadow=”none” column_border_radius=”none” column_link_target=”_self” column_position=”default” gradient_direction=”left_to_right” overlay_strength=”0.3″ width=”1\/1″ tablet_width_inherit=”default” animation_type=”default” bg_image_animation=”none” border_type=”simple” column_border_width=”none” column_border_style=”solid” column_padding_type=”default” gradient_type=”default”][vc_raw_html css=””]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[\/vc_raw_html][\/vc_column][\/vc_row]\n","protected":false},"excerpt":{"rendered":"

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