Optimizing Design of Essential Structural Parameters of Cone Bits

doi:10.3863/j.issn.1000-2634.1997.03.013

西南石油大学学报(自然科学版) ›› 1997, Vol. 19 ›› Issue (3): 70-72.DOI: 10.3863/j.issn.1000-2634.1997.03.013

• 石油机械工程 • Previous Articles Next Articles

Optimizing Design of Essential Structural Parameters of Cone Bits

Wu Ze-bing Hou Ji-kang

(Dept. of Mechanical Engineering, SWPI, Sichuan, 637001)

Received:1996-12-11 Revised:1900-01-01 Online:1997-08-20 Published:1997-08-20
Contact: Wu Ze-bing

Abstract

Abstract: Based on the mechanism of interaction between the bit and rock, the concepts of plane model and spatial one are introduced. The plane model reflects the scraped area by teeth, while the spatial model reflects volume of broken rock by teeth. Two objective functions of optimization are built up and optimal computation to two kinds of bits (ZHP2b and ZHP3a) is carried out using multi-objective optimization method, considering the essential struc-
tural parameters as optimal parameters. The results show that the effectiveness on XHP2b is greater than that on XHP3a. The rate of penetration of optimal bits is increased by 10~20 percent.

Key words: Cone bits, Structure, Model, Optimizing design

CLC Number:

TE821

Wu Ze-bing Hou Ji-kang. Optimizing Design of Essential Structural Parameters of Cone Bits[J]. 西南石油大学学报(自然科学版), 1997, 19(3): 70-72.

0
/ / Recommend

Add to citation manager EndNote|Ris|BibTeX

URL: http://journal15.magtechjournal.com/Jwk_xnzk/EN/10.3863/j.issn.1000-2634.1997.03.013

http://journal15.magtechjournal.com/Jwk_xnzk/EN/Y1997/V19/I3/70

[1]	HUANG Xuri, DAI Yue, XU Yungui, TANG Jing. Seismic Inversion Experiments Based on Deep Learning Algorithm Using Different Datasets [J]. Journal of Southwest Petroleum University(Science & Technology Edition), 2020, 42(6): 16-25.
[2]	ZHONG Yihua, WANG Shuning, LUO Lan, YANG Jinlian, YUE Yongpeng. Knowledge Mining for Oilfield Development Index Prediction Model Using Deep Learning [J]. Journal of Southwest Petroleum University(Science & Technology Edition), 2020, 42(6): 63-74.
[3]	HUANG Cheng, PAN Wenjin. Research and Application of Oil Multi-peak Model Based on Machine Learning [J]. Journal of Southwest Petroleum University(Science & Technology Edition), 2020, 42(6): 75-81.
[4]	YANG Yang, CHENG Yuefei, QIAO Ying, LIU Jiong. A Study on Oil Well Production Prediction Based on Time Series Dynamic Analysis [J]. Journal of Southwest Petroleum University(Science & Technology Edition), 2020, 42(6): 82-88.
[5]	ZHANG Hengru, ZHU Kelin, XU Yuanyuan, QIAO Ying. Granular Computing for Pumping Well Parameter Optimization [J]. Journal of Southwest Petroleum University(Science & Technology Edition), 2020, 42(6): 115-123.
[6]	WANG Hao, ZHANG Lifu, LUO Hao. Study and Application of Multi-parameter Early Warning Model for Gas Wells [J]. Journal of Southwest Petroleum University(Science & Technology Edition), 2020, 42(6): 133-140.
[7]	ZHONG Yuan, LIU Xiaorong, WANG Jie, CHEN Yan, ZHANG Tai. Research of Extraction on Petroleum Unstructured Information Based on Named Entity Recognition [J]. Journal of Southwest Petroleum University(Science & Technology Edition), 2020, 42(6): 165-173.
[8]	YUAN Jingshu, LI Hongqi. Research on MDR Concept System Model and Ontology Representation Standardization [J]. Journal of Southwest Petroleum University(Science & Technology Edition), 2020, 42(6): 174-180.
[9]	PENG Xian, PENG Jun, ZHANG Lianjin, LIN Pan, LAN Xuemei. Characteristics and Main Controlling Factors of the Middle Permian Qixia Formation Reservoir in Shuangyushi Structure [J]. 西南石油大学学报(自然科学版), 2020, 42(5): 1-12.
[10]	ZHAO Xiaoming, FENG Shenglun, TAN Chengpeng, FENG Mochen, TANG Chun. Formation Mechanism and Sedimentary Characteristics of Translational Point Bars [J]. 西南石油大学学报(自然科学版), 2020, 42(4): 22-36.
[11]	NING Fangxing, WANG Xuejun, HAO Xuefeng, YANG Wanqin, DING Juhong. Fine-grained Sedimentary Rock Lithofacies Assemblage Characteristics in Dongying Depression [J]. 西南石油大学学报(自然科学版), 2020, 42(4): 55-65.
[12]	LI Dong, HUANG Xingwen. An Analysis of the Oil Enrichment Factors and Accumulation Models of the Upper Wilcox Formation of Perdido Belt, Mexico [J]. 西南石油大学学报(自然科学版), 2020, 42(4): 73-82.
[13]	MOU Zhonghai, LIU Xue, CHANG Lin, SU Qiu, WU Qianran. Modeling of the Reservoir Architecture of Thin Interbedded Deposits [J]. 西南石油大学学报(自然科学版), 2020, 42(3): 1-12.
[14]	WANG Wei, LI Yongjie, LIU Jiangtao. Exploration a Downhole Visual Automatic Seeker Drilling Technology [J]. 西南石油大学学报(自然科学版), 2020, 42(3): 144-152.
[15]	HE Yingwei, CHEN Guofei, BAO Peinan, TIAN Wei, FENG Deying. Micro-amplitude Structure Identification Method and Its Application in X105 Block [J]. 西南石油大学学报(自然科学版), 2020, 42(3): 43-50.

Optimizing Design of Essential Structural Parameters of Cone Bits

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments