Energy Return on Investment (EROI) for Forty Global Oilfields Using a Detailed Engineering-Based Model of Oil Production
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{"title"=>"Energy return on investment (EROI) for forty global oilfields using a detailed engineering-based model of oil production", "type"=>"journal", "authors"=>[{"first_name"=>"Adam R.", "last_name"=>"Brandt", "scopus_author_id"=>"16030675300"}, {"first_name"=>"Yuchi", "last_name"=>"Sun", "scopus_author_id"=>"56555419900"}, {"first_name"=>"Sharad", "last_name"=>"Bharadwaj", "scopus_author_id"=>"55660428300"}, {"first_name"=>"David", "last_name"=>"Livingston", "scopus_author_id"=>"57095480100"}, {"first_name"=>"Eugene", "last_name"=>"Tan", "scopus_author_id"=>"57095386600"}, {"first_name"=>"Deborah", "last_name"=>"Gordon", "scopus_author_id"=>"57095362000"}], "year"=>2015, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"608044854", "doi"=>"10.1371/journal.pone.0144141", "issn"=>"19326203", "sgr"=>"84957052381", "scopus"=>"2-s2.0-84957052381"}, "id"=>"ca08b905-eb0c-379f-bea1-378980906eef", "abstract"=>"<p>Studies of the energy return on investment (EROI) for oil production generally rely on aggregated statistics for large regions or countries. In order to better understand the drivers of the energy productivity of oil production, we use a novel approach that applies a detailed field-level engineering model of oil and gas production to estimate energy requirements of drilling, producing, processing, and transporting crude oil. We examine 40 global oilfields, utilizing detailed data for each field from hundreds of technical and scientific data sources. Resulting net energy return (NER) ratios for studied oil fields range from ≈2 to ≈100 MJ crude oil produced per MJ of total fuels consumed. External energy return (EER) ratios, which compare energy produced to energy consumed from external sources, exceed 1000:1 for fields that are largely self-sufficient. The lowest energy returns are found to come from thermally-enhanced oil recovery technologies. Results are generally insensitive to reasonable ranges of assumptions explored in sensitivity analysis. Fields with very large associated gas production are sensitive to assumptions about surface fluids processing due to the shifts in energy consumed under different gas treatment configurations. This model does not currently include energy invested in building oilfield capital equipment (e.g., drilling rigs), nor does it include other indirect energy uses such as labor or services.</p>", "link"=>"http://www.mendeley.com/research/energy-return-investment-eroi-forty-global-oilfields-using-detailed-engineeringbased-model-oil-produ", "reader_count"=>5, "reader_count_by_academic_status"=>{"Student > Ph. D. Student"=>4, "Student > Master"=>1}, "reader_count_by_user_role"=>{"Student > Ph. D. Student"=>4, "Student > Master"=>1}, "reader_count_by_subject_area"=>{"Engineering"=>3, "Economics, Econometrics and Finance"=>1, "Energy"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>3}, "Energy"=>{"Energy"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}}, "reader_count_by_country"=>{"United Kingdom"=>1}, "group_count"=>0}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/2615068"], "description"=>"<p>(a) drilling energy sensitivity case and (b) processing configuration sensitivity cases (see case definitions in text).</p>", "links"=>[], "tags"=>["gas production", "oil fields range", "EROI", "eer", "Oil Production Studies", "energy return", "mj", "gas treatment configurations", "External energy return", "ner", "surface fluids processing", "estimate energy requirements", "oil production", "building oilfield capital equipment"], "article_id"=>1629136, "categories"=>["Biological Sciences"], "users"=>["Adam R. Brandt", "Yuchi Sun", "Sharad Bharadwaj", "David Livingston", "Eugene Tan", "Deborah Gordon"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0144141.g004", "stats"=>{"downloads"=>0, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sensitivity_of_all_studied_fields_to_two_varied_parameters_/1629136", "title"=>"Sensitivity of all studied fields to two varied parameters.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-05 14:52:54"}
  • {"files"=>["https://ndownloader.figshare.com/files/2615069"], "description"=>"<p>Sensitivity of low-NER thermal oil recovery fields to assumptions about steam generation efficiencies and configurations.</p>", "links"=>[], "tags"=>["gas production", "oil fields range", "EROI", "eer", "Oil Production Studies", "energy return", "mj", "gas treatment configurations", "External energy return", "ner", "surface fluids processing", "estimate energy requirements", "oil production", "building oilfield capital equipment"], "article_id"=>1629137, "categories"=>["Biological Sciences"], "users"=>["Adam R. Brandt", "Yuchi Sun", "Sharad Bharadwaj", "David Livingston", "Eugene Tan", "Deborah Gordon"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0144141.g005", "stats"=>{"downloads"=>3, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sensitivity_of_low_NER_thermal_oil_recovery_fields_to_assumptions_about_steam_generation_efficiencies_and_configurations_/1629137", "title"=>"Sensitivity of low-NER thermal oil recovery fields to assumptions about steam generation efficiencies and configurations.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-05 14:52:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/2615070"], "description"=>"<div><p>Studies of the energy return on investment (EROI) for oil production generally rely on aggregated statistics for large regions or countries. In order to better understand the drivers of the energy productivity of oil production, we use a novel approach that applies a detailed field-level engineering model of oil and gas production to estimate energy requirements of drilling, producing, processing, and transporting crude oil. We examine 40 global oilfields, utilizing detailed data for each field from hundreds of technical and scientific data sources. Resulting net energy return (NER) ratios for studied oil fields range from ≈2 to ≈100 MJ crude oil produced per MJ of total fuels consumed. External energy return (EER) ratios, which compare energy produced to energy consumed from external sources, exceed 1000:1 for fields that are largely self-sufficient. The lowest energy returns are found to come from thermally-enhanced oil recovery technologies. Results are generally insensitive to reasonable ranges of assumptions explored in sensitivity analysis. Fields with very large associated gas production are sensitive to assumptions about surface fluids processing due to the shifts in energy consumed under different gas treatment configurations. This model does not currently include energy invested in building oilfield capital equipment (e.g., drilling rigs), nor does it include other indirect energy uses such as labor or services.</p></div>", "links"=>[], "tags"=>["gas production", "oil fields range", "EROI", "eer", "Oil Production Studies", "energy return", "mj", "gas treatment configurations", "External energy return", "ner", "surface fluids processing", "estimate energy requirements", "oil production", "building oilfield capital equipment"], "article_id"=>1629138, "categories"=>["Biological Sciences"], "users"=>["Adam R. Brandt", "Yuchi Sun", "Sharad Bharadwaj", "David Livingston", "Eugene Tan", "Deborah Gordon"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0144141", "stats"=>{"downloads"=>5, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Energy_Return_on_Investment_EROI_for_Forty_Global_Oilfields_Using_a_Detailed_Engineering_Based_Model_of_Oil_Production_/1629138", "title"=>"Energy Return on Investment (EROI) for Forty Global Oilfields Using a Detailed Engineering-Based Model of Oil Production", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2016-01-05 14:52:53"}
  • {"files"=>["https://ndownloader.figshare.com/files/2615065"], "description"=>"<p>System diagram with flow labels as used in equations. Consistent assumptions about type of energy across fields allows easier characterization of upstream emissions.</p>", "links"=>[], "tags"=>["gas production", "oil fields range", "EROI", "eer", "Oil Production Studies", "energy return", "mj", "gas treatment configurations", "External energy return", "ner", "surface fluids processing", "estimate energy requirements", "oil production", "building oilfield capital equipment"], "article_id"=>1629133, "categories"=>["Biological Sciences"], "users"=>["Adam R. Brandt", "Yuchi Sun", "Sharad Bharadwaj", "David Livingston", "Eugene Tan", "Deborah Gordon"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0144141.g001", "stats"=>{"downloads"=>1, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_System_diagram_with_flow_labels_as_used_in_equations_Consistent_assumptions_about_type_of_energy_across_fields_allows_easier_characterization_of_upstream_emissions_/1629133", "title"=>"System diagram with flow labels as used in equations. Consistent assumptions about type of energy across fields allows easier characterization of upstream emissions.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-05 14:52:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/2615066"], "description"=>"<p><i>NER</i><sub><i>tot</i></sub> is always greater than or equal to <i>NER</i><sub><i>oil</i></sub>. <i>NER</i><sub><i>tot</i>, <i>flare</i></sub> adds in energy content of flared gases as consumed energy (see discussion in main text).</p>", "links"=>[], "tags"=>["gas production", "oil fields range", "EROI", "eer", "Oil Production Studies", "energy return", "mj", "gas treatment configurations", "External energy return", "ner", "surface fluids processing", "estimate energy requirements", "oil production", "building oilfield capital equipment"], "article_id"=>1629134, "categories"=>["Biological Sciences"], "users"=>["Adam R. Brandt", "Yuchi Sun", "Sharad Bharadwaj", "David Livingston", "Eugene Tan", "Deborah Gordon"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0144141.g002", "stats"=>{"downloads"=>1, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Total_net_energy_ratio_NER_tot_and_oil_specific_net_energy_ratio_NER_oil_for_studied_global_oil_fields_/1629134", "title"=>"Total net energy ratio <i>NER</i><sub><i>tot</i></sub> and oil-specific net energy ratio <i>NER</i><sub><i>oil</i></sub> for studied global oil fields.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-05 14:52:52"}
  • {"files"=>["https://ndownloader.figshare.com/files/2615067"], "description"=>"<p>Note logarithmic scale due to very wide variation in <i>EER</i> values.</p>", "links"=>[], "tags"=>["gas production", "oil fields range", "EROI", "eer", "Oil Production Studies", "energy return", "mj", "gas treatment configurations", "External energy return", "ner", "surface fluids processing", "estimate energy requirements", "oil production", "building oilfield capital equipment"], "article_id"=>1629135, "categories"=>["Biological Sciences"], "users"=>["Adam R. Brandt", "Yuchi Sun", "Sharad Bharadwaj", "David Livingston", "Eugene Tan", "Deborah Gordon"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0144141.g003", "stats"=>{"downloads"=>1, "page_views"=>0, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Total_external_energy_ratio_EER_tot_and_oil_specific_external_energy_ratio_EER_oil_for_studied_global_oil_fields_/1629135", "title"=>"Total external energy ratio <i>EER</i><sub><i>tot</i></sub> and oil-specific external energy ratio <i>EER</i><sub><i>oil</i></sub> for studied global oil fields.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2016-01-05 14:52:52"}

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