<?xml version="1.0" encoding="UTF-8"?><doi_batch xmlns="http://www.crossref.org/grant_id/0.2.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.crossref.org/grant_id/0.2.0 https://gitlab.com/crossref/schema/-/raw/master/schemas/grant_id0.2.0.xsd" version="0.2.0">  <head>    <doi_batch_id>batch_auto_20260713</doi_batch_id>    <timestamp>202607131256465730</timestamp>    <depositor>      <depositor_name>BOEM ESP geoESPIS</depositor_name>      <email_address>ESPIS@boem.gov</email_address>    </depositor>    <registrant>Bureau of Ocean Energy Management</registrant>  </head>  <body>    <grant>      <project>        <project-title xml:lang="en">Oil Spill Occurrence Estimators for Onshore Alaska North Slope and Cook Inlet Crude and Refined Oil Spills</project-title>          <investigators>          <person role="investigator">            <alternateName>Nuka Research and Planning Group, LLC</alternateName>            <affiliation>              <institution country="US">Nuka Research and Planning Group, LLC</institution>            </affiliation>          </person>          </investigators>        <description xml:lang="en">Under contract to the Bureau of Ocean Energy Management (BOEM), Nuka Research and Planning Group, LLC developed statistical methods to estimate oil spill occurrence based on past spills in the Alaska North Slope and in Cook Inlet. While all spills larger than one barrel from the respective datasets were characterized, only spills from 1996-2019 were used to evaluate trends and develop the occurrence estimators. The following independent variables were considered: annual volume of gas produced from gas wells, annual volume of oil produced from oil wells, annual volume of water produced from oil wells, and the average inflation-adjusted price of Alaskan crude each year. A suitable regression model was identified for the annual number of spills overall and crude spills for each area using oil production. The North Slope model also included adjusted price as independent variables. By contrast, it was not possible to develop a regression model to estimate the annual volume of oil spills. Instead, a bootstrapping method and Monte Carlo simulation was used to estimate the spill volume. Similarly, the number of refined spills did not correspond well with any of the independent variables considered.</description>        <award_amount currency="USD">224658</award_amount>        <funding amount="224658" currency="USD" funding-percentage="100" funding-type="contract">          <funder-name>U.S. Department of the Interior, Bureau of Ocean Energy Management, Environmental Studies Program</funder-name>          <funder-id>https://doi.org/10.13039/100012475</funder-id>        </funding>        <award-dates start-date="2018-11-02" end-date="2021-03-31"/>      </project>      <award-number>M0119F0003</award-number>      <doi_data>        <doi>10.67297/9A1E20</doi>        <resource>https://boem.gov/awardpages/100256</resource>      </doi_data>    </grant>  </body></doi_batch>