Predicting S-Wave Velocity from Wire-Line Logs for Organic-Rich Rocks
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作者:
Liu, Zhishui
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Changan Univ, Coll Geol Engn & Geomat, Xian 710064, Shaanxi, Peoples R ChinaChangan Univ, Coll Geol Engn & Geomat, Xian 710064, Shaanxi, Peoples R China
Liu, Zhishui
[1
]
Lu, Huan
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机构:
China Natl Offshore Oil Corp, Bohai Oilfield Res Inst, Tianjin 300459, Peoples R ChinaChangan Univ, Coll Geol Engn & Geomat, Xian 710064, Shaanxi, Peoples R China
Lu, Huan
[2
]
Bao, Qianzong
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Changan Univ, Coll Geol Engn & Geomat, Xian 710064, Shaanxi, Peoples R ChinaChangan Univ, Coll Geol Engn & Geomat, Xian 710064, Shaanxi, Peoples R China
Bao, Qianzong
[1
]
Liu, Junzhou
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SINOPEC, Res Inst Petr Explorat & Dev, Beijing 100083, Peoples R ChinaChangan Univ, Coll Geol Engn & Geomat, Xian 710064, Shaanxi, Peoples R China
Liu, Junzhou
[3
]
Yu, Hongyu
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SINOPEC, Taizhou Oil Prod Plant East China Oil & Gas Co, Taizhou 225300, Jiangsu, Peoples R ChinaChangan Univ, Coll Geol Engn & Geomat, Xian 710064, Shaanxi, Peoples R China
Yu, Hongyu
[4
]
机构:
[1] Changan Univ, Coll Geol Engn & Geomat, Xian 710064, Shaanxi, Peoples R China
[2] China Natl Offshore Oil Corp, Bohai Oilfield Res Inst, Tianjin 300459, Peoples R China
[3] SINOPEC, Res Inst Petr Explorat & Dev, Beijing 100083, Peoples R China
[4] SINOPEC, Taizhou Oil Prod Plant East China Oil & Gas Co, Taizhou 225300, Jiangsu, Peoples R China
Lacking of S-wave velocity in logging will negatively affect the process of reservoir prediction and formation evaluation for organic rich rock reservoir. In this paper, a simple but effective method is presented to predict the S-wave velocity from P-wave velocity based on the combination of the critical porosity consolidation coefficient (CPCC) model with dual-variable parameters and quantum particle swarm optimization (QPSO) algorithm. In the presented method, the P-and S-wave velocities of organic-rich rock are linked by consolidation coefficient and critical porosity. Then, the error between the measured and calculated P-wave velocity is used to establish the inverse objective function. Moreover, the QPSO algorithm is introduced to invert the critical porosity and consolidation coefficient. Finally, the S-wave velocity can be predicted using the inverted parameters. Compared with two existing single-parameter adaptive methods, the predicted S-wave velocity of the proposed method is superior, which can be satisfactorily implemented for laboratory measurement and on logging data.