Optimization of methane use in cyclic solvent injection for heavy-oil recovery after primary production through experimental and numerical studies
Although cold heavy oil production with sands (CHOPS) is an economically attractive method, ultimate recovery does not exceed 15%. Cyclic solvent injection (CSI) has been under consideration as a follow-up EOR application in the industry. This method targets extracting large amounts of remaining oil...
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description | Although cold heavy oil production with sands (CHOPS) is an economically attractive method, ultimate recovery does not exceed 15%. Cyclic solvent injection (CSI) has been under consideration as a follow-up EOR application in the industry. This method targets extracting large amounts of remaining oil in the matrix by solvent diffusion, taking advantage of its high contact area with wormholes. Methane and propane are two potential solvents to be used in this practice. Methane is preferred due to its availability and stronger foaming characteristics, while propane has lower foaming but better mixing capability.
A far-reaching -core to field scale- study was conducted in this paper to test out the potential of pure methane and its mixture with propane as well as CO2 as prospective CSI solvents. After the petro-physical properties of the sand-pack (1.5 m-length and 5 cm-diameter) were measured, live oil (saturated with methane and methane-propane mixture at different ratios) production was carried out with certain pressure decline rates: −0.51 psi/min from 500 to 190 psi and −0.23 psi/min from 190 to 70 psi. Pressure data with time was monitored through eight equally spaced transducers. The solution GOR from the live oil saturated with methane vs. pressure was matched using the Peng-Robinson EOS (Peng and Robinson, 1976) method. The data points starting injection period (representing equilibrium condition) were fitted to develop K values using the Crookston equation. These matched data were carried to a field scale model to analyze the CSI performance for methane. In field scale modeling, 15-well data from a CHOPS field in Alberta, Canada were history matched and 6-cycle CSI performances were followed as post-CHOPS with different well patterns (central, peripheral, all-wells).
As a result of these experiments, methane showed about 14% oil recovery but with additional CO2 huff ‘n’ puff, around 15% recovery was added, totaling 29% recovery. Methane-propane mixture resulted in a lower oil recovery of about 5% due to decreased foamy effect. Valid core-scale simulation was completed by tuning K-values and considering non-equilibrium or equilibrium impact depending on solvent type, showing mostly less than 5% error. In field scale modeling, central and peripheral well patterns yielded oil recoveries consistent with the experiments while all-well huff ‘n’ puff- type pattern showed a slightly higher value.
Based on the outcome of the methane and methane-propane mixture |
doi_str_mv | 10.1016/j.fuel.2017.11.064 |
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A far-reaching -core to field scale- study was conducted in this paper to test out the potential of pure methane and its mixture with propane as well as CO2 as prospective CSI solvents. After the petro-physical properties of the sand-pack (1.5 m-length and 5 cm-diameter) were measured, live oil (saturated with methane and methane-propane mixture at different ratios) production was carried out with certain pressure decline rates: −0.51 psi/min from 500 to 190 psi and −0.23 psi/min from 190 to 70 psi. Pressure data with time was monitored through eight equally spaced transducers. The solution GOR from the live oil saturated with methane vs. pressure was matched using the Peng-Robinson EOS (Peng and Robinson, 1976) method. The data points starting injection period (representing equilibrium condition) were fitted to develop K values using the Crookston equation. These matched data were carried to a field scale model to analyze the CSI performance for methane. In field scale modeling, 15-well data from a CHOPS field in Alberta, Canada were history matched and 6-cycle CSI performances were followed as post-CHOPS with different well patterns (central, peripheral, all-wells).
As a result of these experiments, methane showed about 14% oil recovery but with additional CO2 huff ‘n’ puff, around 15% recovery was added, totaling 29% recovery. Methane-propane mixture resulted in a lower oil recovery of about 5% due to decreased foamy effect. Valid core-scale simulation was completed by tuning K-values and considering non-equilibrium or equilibrium impact depending on solvent type, showing mostly less than 5% error. In field scale modeling, central and peripheral well patterns yielded oil recoveries consistent with the experiments while all-well huff ‘n’ puff- type pattern showed a slightly higher value.
Based on the outcome of the methane and methane-propane mixture experiments, it was of more importance to further study the way to enhance the foaminess in methane-live oil recovery. Different pressure depletion rates, namely −0.23, −0.51, and −1.53 psi/min, were applied and more oil was produced with increasing depletion rates. These experimental results were simulated at the core scale and the change of reaction coefficients was considered with varying decline rates. In field-scale modelling, sensitivity analyses were done with a variety of scenarios by changing injection/soaking period and pressure decline rates. The ratio of injection to soaking period was observed to be more critical than the injection period itself in terms of production efficiency. Also, the influence of pressure depletion rate as a new constraint in the simulation work was studied.</description><identifier>ISSN: 0016-2361</identifier><identifier>EISSN: 1873-7153</identifier><identifier>DOI: 10.1016/j.fuel.2017.11.064</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Actual field case ; Carbon dioxide ; Computer simulation ; Constraint modelling ; Cyclic solvent injection ; Data points ; Data processing ; Depletion ; Economic conditions ; Enhanced oil recovery ; Foaming ; Foamy oil core-flooding ; Injection ; Methane ; Numerical analysis ; Oil and gas exploration ; Oil and gas production ; Oil recovery ; Optimization ; Physical properties ; Post-CHOPS heavy-oil recovery ; Pressure ; Pressure depletion tests ; Primary production ; Propane ; Propane and methane mixture ; Scale models ; Sensitivity analysis ; Soaking ; Solvents ; Studies ; Transducers ; Water wells ; Well data ; Wormholes</subject><ispartof>Fuel (Guildford), 2018-02, Vol.214, p.457-470</ispartof><rights>2017 Elsevier Ltd</rights><rights>Copyright Elsevier BV Feb 15, 2018</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c365t-92156bf19e4773bbcd5c28c367a279562a5b5d1f73236852788bde98d8f1e7fe3</citedby><cites>FETCH-LOGICAL-c365t-92156bf19e4773bbcd5c28c367a279562a5b5d1f73236852788bde98d8f1e7fe3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0016236117314667$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65534</link.rule.ids></links><search><creatorcontrib>Soh, Y.</creatorcontrib><creatorcontrib>Rangriz-Shokri, A.</creatorcontrib><creatorcontrib>Babadagli, T.</creatorcontrib><title>Optimization of methane use in cyclic solvent injection for heavy-oil recovery after primary production through experimental and numerical studies</title><title>Fuel (Guildford)</title><description>Although cold heavy oil production with sands (CHOPS) is an economically attractive method, ultimate recovery does not exceed 15%. Cyclic solvent injection (CSI) has been under consideration as a follow-up EOR application in the industry. This method targets extracting large amounts of remaining oil in the matrix by solvent diffusion, taking advantage of its high contact area with wormholes. Methane and propane are two potential solvents to be used in this practice. Methane is preferred due to its availability and stronger foaming characteristics, while propane has lower foaming but better mixing capability.
A far-reaching -core to field scale- study was conducted in this paper to test out the potential of pure methane and its mixture with propane as well as CO2 as prospective CSI solvents. After the petro-physical properties of the sand-pack (1.5 m-length and 5 cm-diameter) were measured, live oil (saturated with methane and methane-propane mixture at different ratios) production was carried out with certain pressure decline rates: −0.51 psi/min from 500 to 190 psi and −0.23 psi/min from 190 to 70 psi. Pressure data with time was monitored through eight equally spaced transducers. The solution GOR from the live oil saturated with methane vs. pressure was matched using the Peng-Robinson EOS (Peng and Robinson, 1976) method. The data points starting injection period (representing equilibrium condition) were fitted to develop K values using the Crookston equation. These matched data were carried to a field scale model to analyze the CSI performance for methane. In field scale modeling, 15-well data from a CHOPS field in Alberta, Canada were history matched and 6-cycle CSI performances were followed as post-CHOPS with different well patterns (central, peripheral, all-wells).
As a result of these experiments, methane showed about 14% oil recovery but with additional CO2 huff ‘n’ puff, around 15% recovery was added, totaling 29% recovery. Methane-propane mixture resulted in a lower oil recovery of about 5% due to decreased foamy effect. Valid core-scale simulation was completed by tuning K-values and considering non-equilibrium or equilibrium impact depending on solvent type, showing mostly less than 5% error. In field scale modeling, central and peripheral well patterns yielded oil recoveries consistent with the experiments while all-well huff ‘n’ puff- type pattern showed a slightly higher value.
Based on the outcome of the methane and methane-propane mixture experiments, it was of more importance to further study the way to enhance the foaminess in methane-live oil recovery. Different pressure depletion rates, namely −0.23, −0.51, and −1.53 psi/min, were applied and more oil was produced with increasing depletion rates. These experimental results were simulated at the core scale and the change of reaction coefficients was considered with varying decline rates. In field-scale modelling, sensitivity analyses were done with a variety of scenarios by changing injection/soaking period and pressure decline rates. The ratio of injection to soaking period was observed to be more critical than the injection period itself in terms of production efficiency. Also, the influence of pressure depletion rate as a new constraint in the simulation work was studied.</description><subject>Actual field case</subject><subject>Carbon dioxide</subject><subject>Computer simulation</subject><subject>Constraint modelling</subject><subject>Cyclic solvent injection</subject><subject>Data points</subject><subject>Data processing</subject><subject>Depletion</subject><subject>Economic conditions</subject><subject>Enhanced oil recovery</subject><subject>Foaming</subject><subject>Foamy oil core-flooding</subject><subject>Injection</subject><subject>Methane</subject><subject>Numerical analysis</subject><subject>Oil and gas exploration</subject><subject>Oil and gas production</subject><subject>Oil recovery</subject><subject>Optimization</subject><subject>Physical properties</subject><subject>Post-CHOPS heavy-oil recovery</subject><subject>Pressure</subject><subject>Pressure depletion tests</subject><subject>Primary production</subject><subject>Propane</subject><subject>Propane and methane mixture</subject><subject>Scale models</subject><subject>Sensitivity analysis</subject><subject>Soaking</subject><subject>Solvents</subject><subject>Studies</subject><subject>Transducers</subject><subject>Water wells</subject><subject>Well data</subject><subject>Wormholes</subject><issn>0016-2361</issn><issn>1873-7153</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp9kM9O3DAQxq2qSN0CL9CTJc4JnmQdO1IvCFFAQuICZ8uxx11H2XhrOyu2j9EnrpflzGk0M983f36E_ABWA4PueqzdglPdMBA1QM269ReyAinaSgBvv5IVK6qqaTv4Rr6nNDLGhOTrFfn3vMt-6__q7MNMg6NbzBs9I10SUj9TczCTNzSFaY9zLpURzbvUhUg3qPeHKviJRjRhj_FAtcsY6S76rS7ZLga7nPR5E8Pye0PxbYelW4bpierZ0nnZloIpWcqL9ZguyJnTU8LLj3hOXn_dvdw-VE_P94-3N0-VaTueq74B3g0OelwL0Q6Dsdw0svSEbkTPu0bzgVtwoi1vS94IKQeLvbTSAQqH7Tm5Os0tV_5ZMGU1hiXOZaWCXgrBRL-GompOKhNDShGd-nhOAVNH9mpUR_bqyF4BqMK-mH6eTFju33uMKhmPs0HrC6msbPCf2f8D4o2RTg</recordid><startdate>20180215</startdate><enddate>20180215</enddate><creator>Soh, Y.</creator><creator>Rangriz-Shokri, A.</creator><creator>Babadagli, T.</creator><general>Elsevier Ltd</general><general>Elsevier BV</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7T7</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>C1K</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope></search><sort><creationdate>20180215</creationdate><title>Optimization of methane use in cyclic solvent injection for heavy-oil recovery after primary production through experimental and numerical studies</title><author>Soh, Y. ; Rangriz-Shokri, A. ; Babadagli, T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c365t-92156bf19e4773bbcd5c28c367a279562a5b5d1f73236852788bde98d8f1e7fe3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Actual field case</topic><topic>Carbon dioxide</topic><topic>Computer simulation</topic><topic>Constraint modelling</topic><topic>Cyclic solvent injection</topic><topic>Data points</topic><topic>Data processing</topic><topic>Depletion</topic><topic>Economic conditions</topic><topic>Enhanced oil recovery</topic><topic>Foaming</topic><topic>Foamy oil core-flooding</topic><topic>Injection</topic><topic>Methane</topic><topic>Numerical analysis</topic><topic>Oil and gas exploration</topic><topic>Oil and gas production</topic><topic>Oil recovery</topic><topic>Optimization</topic><topic>Physical properties</topic><topic>Post-CHOPS heavy-oil recovery</topic><topic>Pressure</topic><topic>Pressure depletion tests</topic><topic>Primary production</topic><topic>Propane</topic><topic>Propane and methane mixture</topic><topic>Scale models</topic><topic>Sensitivity analysis</topic><topic>Soaking</topic><topic>Solvents</topic><topic>Studies</topic><topic>Transducers</topic><topic>Water wells</topic><topic>Well data</topic><topic>Wormholes</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Soh, Y.</creatorcontrib><creatorcontrib>Rangriz-Shokri, A.</creatorcontrib><creatorcontrib>Babadagli, T.</creatorcontrib><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Fuel (Guildford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Soh, Y.</au><au>Rangriz-Shokri, A.</au><au>Babadagli, T.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimization of methane use in cyclic solvent injection for heavy-oil recovery after primary production through experimental and numerical studies</atitle><jtitle>Fuel (Guildford)</jtitle><date>2018-02-15</date><risdate>2018</risdate><volume>214</volume><spage>457</spage><epage>470</epage><pages>457-470</pages><issn>0016-2361</issn><eissn>1873-7153</eissn><abstract>Although cold heavy oil production with sands (CHOPS) is an economically attractive method, ultimate recovery does not exceed 15%. Cyclic solvent injection (CSI) has been under consideration as a follow-up EOR application in the industry. This method targets extracting large amounts of remaining oil in the matrix by solvent diffusion, taking advantage of its high contact area with wormholes. Methane and propane are two potential solvents to be used in this practice. Methane is preferred due to its availability and stronger foaming characteristics, while propane has lower foaming but better mixing capability.
A far-reaching -core to field scale- study was conducted in this paper to test out the potential of pure methane and its mixture with propane as well as CO2 as prospective CSI solvents. After the petro-physical properties of the sand-pack (1.5 m-length and 5 cm-diameter) were measured, live oil (saturated with methane and methane-propane mixture at different ratios) production was carried out with certain pressure decline rates: −0.51 psi/min from 500 to 190 psi and −0.23 psi/min from 190 to 70 psi. Pressure data with time was monitored through eight equally spaced transducers. The solution GOR from the live oil saturated with methane vs. pressure was matched using the Peng-Robinson EOS (Peng and Robinson, 1976) method. The data points starting injection period (representing equilibrium condition) were fitted to develop K values using the Crookston equation. These matched data were carried to a field scale model to analyze the CSI performance for methane. In field scale modeling, 15-well data from a CHOPS field in Alberta, Canada were history matched and 6-cycle CSI performances were followed as post-CHOPS with different well patterns (central, peripheral, all-wells).
As a result of these experiments, methane showed about 14% oil recovery but with additional CO2 huff ‘n’ puff, around 15% recovery was added, totaling 29% recovery. Methane-propane mixture resulted in a lower oil recovery of about 5% due to decreased foamy effect. Valid core-scale simulation was completed by tuning K-values and considering non-equilibrium or equilibrium impact depending on solvent type, showing mostly less than 5% error. In field scale modeling, central and peripheral well patterns yielded oil recoveries consistent with the experiments while all-well huff ‘n’ puff- type pattern showed a slightly higher value.
Based on the outcome of the methane and methane-propane mixture experiments, it was of more importance to further study the way to enhance the foaminess in methane-live oil recovery. Different pressure depletion rates, namely −0.23, −0.51, and −1.53 psi/min, were applied and more oil was produced with increasing depletion rates. These experimental results were simulated at the core scale and the change of reaction coefficients was considered with varying decline rates. In field-scale modelling, sensitivity analyses were done with a variety of scenarios by changing injection/soaking period and pressure decline rates. The ratio of injection to soaking period was observed to be more critical than the injection period itself in terms of production efficiency. Also, the influence of pressure depletion rate as a new constraint in the simulation work was studied.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.fuel.2017.11.064</doi><tpages>14</tpages></addata></record> |
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subjects | Actual field case Carbon dioxide Computer simulation Constraint modelling Cyclic solvent injection Data points Data processing Depletion Economic conditions Enhanced oil recovery Foaming Foamy oil core-flooding Injection Methane Numerical analysis Oil and gas exploration Oil and gas production Oil recovery Optimization Physical properties Post-CHOPS heavy-oil recovery Pressure Pressure depletion tests Primary production Propane Propane and methane mixture Scale models Sensitivity analysis Soaking Solvents Studies Transducers Water wells Well data Wormholes |
title | Optimization of methane use in cyclic solvent injection for heavy-oil recovery after primary production through experimental and numerical studies |
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