TY - JOUR
T1 - A sustainable lean production framework based on inverse DEA for mitigating gas flaring
AU - Orisaremi, Kayode Kelvin
AU - Chan, Tung Sun
AU - Chung, Sai Ho
AU - Fu, Xiaowen
N1 - Funding Information:
The work described in this paper was supported by The Hong Kong Polytechnic University under student account code 1-RLLY. The authors also would like to thank The Hong Kong Polytechnic University Research Committee for financial and technical support.
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/11/15
Y1 - 2022/11/15
N2 - The gas flaring process remains a significant contributor to climate change due to the release of greenhouse gases. Additionally, it denies oil-producing nations access to affordable energy sources. With climate change gaining momentum and in accordance with the global gas flaring reduction partnership (GGFR), oil and gas production managers must adopt an approach that can be both environmentally and economically beneficial. As such, this study proposes a novel application of the inverse data envelopment analysis (DEA) model for implementing lean production practices in the petroleum industry. Using inverse DEA methodology, a three-stage inverse problem involving selected oil-producing nations during the 2015 production year was solved. Stage one found that by incorporating lean practices, all the efficient producers were able to increase oil production by 50,000 barrels without increasing their current levels of flared gas. For the second stage, a reduction in gas flaring was imposed on the efficient producers to achieve the same production targets as stage one. Gas flaring reductions for Angola, Iraq, Libya, and Nigeria were computed to be 13.75%, 4.59%, 25.24%, and 54.93 %, respectively. A simple cycle gas turbine, such as the GT13E2, was used for all four nations to convert these reductions into gross power outputs of 300 MW, 150 MW, 450 MW, and 2250 MW, respectively, with Nigeria clearly benefiting the most. In the third stage, the concept of lean potential growth was integrated into an improved model to rank efficient oil producers. Saudi Arabia was found to be the most efficient producer, partly explaining why no reductions in gas flaring were obtainable for the nation in stage two. Based on our findings, we recommend the proposed models and new concepts for improving operational sustainability in the petroleum industry.
AB - The gas flaring process remains a significant contributor to climate change due to the release of greenhouse gases. Additionally, it denies oil-producing nations access to affordable energy sources. With climate change gaining momentum and in accordance with the global gas flaring reduction partnership (GGFR), oil and gas production managers must adopt an approach that can be both environmentally and economically beneficial. As such, this study proposes a novel application of the inverse data envelopment analysis (DEA) model for implementing lean production practices in the petroleum industry. Using inverse DEA methodology, a three-stage inverse problem involving selected oil-producing nations during the 2015 production year was solved. Stage one found that by incorporating lean practices, all the efficient producers were able to increase oil production by 50,000 barrels without increasing their current levels of flared gas. For the second stage, a reduction in gas flaring was imposed on the efficient producers to achieve the same production targets as stage one. Gas flaring reductions for Angola, Iraq, Libya, and Nigeria were computed to be 13.75%, 4.59%, 25.24%, and 54.93 %, respectively. A simple cycle gas turbine, such as the GT13E2, was used for all four nations to convert these reductions into gross power outputs of 300 MW, 150 MW, 450 MW, and 2250 MW, respectively, with Nigeria clearly benefiting the most. In the third stage, the concept of lean potential growth was integrated into an improved model to rank efficient oil producers. Saudi Arabia was found to be the most efficient producer, partly explaining why no reductions in gas flaring were obtainable for the nation in stage two. Based on our findings, we recommend the proposed models and new concepts for improving operational sustainability in the petroleum industry.
KW - Gas flaring
KW - Climate change
KW - Lean production
KW - Gas turbine
KW - Gross power output
KW - Inverse DEA
UR - http://www.scopus.com/inward/record.url?scp=85132697691&partnerID=8YFLogxK
U2 - 10.1016/j.eswa.2022.117856
DO - 10.1016/j.eswa.2022.117856
M3 - Journal article
SN - 0957-4174
VL - 206
JO - Expert Systems with Applications
JF - Expert Systems with Applications
M1 - 117856
ER -