Monitoring the Geometry Morphology of Complex Hydraulic Fracture Network by Using a Multiobjective Inversion Algorithm Based on Decomposition

Liming Zhang, Lili Xue, Chenyu Cui, Ji Qi, Jijia Sun, Xingyu Zhou, Qinyang Dai and Kai Zhang
Additional contact information
Liming Zhang: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
Lili Xue: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
Chenyu Cui: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
Ji Qi: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
Jijia Sun: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
Xingyu Zhou: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
Qinyang Dai: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
Kai Zhang: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China

Energies, 2021, vol. 14, issue 16, 1-21

Abstract: The fracturing technique is widely used in many fields. Fracture has a greater impact on the movement of fluids in formations. Knowing information about a fracture is key to judging its effect, but detailed information about complex fracture networks is difficult to obtain. In this paper, we propose a new method to describe the shape of a complex fracture network. This method is based on microseismic results and uses the L-system to establish a method for characterizing a complex fracture network. The method also combines with decomposition to construct a new method called the multiobjective fracture network inversion algorithm based on decomposition (MOFNIAD). The coverage of microseismic monitoring results and the degree of fitting of production data are the two objective functions of the inversion fracture network. The multiobjective fracture network inversion algorithm can be optimized to obtain multiple optimal solutions that meet different target weights. Therefore, this paper established a multischeme decision method that approached the ideal solution, sorting technology and AHP to provide theoretical guidance for finding a more ideal fracture network. According to the error of microseismic monitoring results, we established two cases of fracture to verify the proposed method. Judging from the results of the examples, the fracture network finally obtained was similar to actual fractures.

Keywords: tight reservoir; hydraulic fracture monitoring; multiobjective optimization; complex fracture network inversion (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/16/5216/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/16/5216/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:16:p:5216-:d:620253

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().