Analytical Model for Predicting Productivity of Radial-Lateral Wells
Boyun Guo,
Rashid Shaibu and
Xu Yang
Additional contact information
Boyun Guo: Department of Petroleum Engineering, University of Louisiana at Lafayette, Lafayette, LA 70504, USA
Rashid Shaibu: Department of Petroleum Engineering, University of Louisiana at Lafayette, Lafayette, LA 70504, USA
Xu Yang: Department of Petroleum Engineering, University of Louisiana at Lafayette, Lafayette, LA 70504, USA
Energies, 2020, vol. 13, issue 23, 1-16
Abstract:
An analytical model for predicting the productivity of Radial-lateral wells (RLW) drilled using radial jet drilling technology was developed in this work. The model assumes uniformly distributed equal-geometry laterals draining oil or gas under pseudo-steady state flow conditions within the lateral-reached drainage area. A numerical simulation and production data from three field cases of RLW were used to compare and validate the model. The result indicates that the model overestimates the well production rates for wells by 7.7%, 3.25%, and 8.8%, respectively. The error is attributed to several sources including, lack of data for well skin factor, uncertainty of horizontal permeability ( k H ) in the well area, uncertainty of permeability anisotropy ( I ani ), and uncertainty in bottom hole pressure (pw). Error analysis of uncertainties in k H , I ani , and pw showed that the model could predict productivity well with an acceptable error (10%) over practical ranges of these parameter values. Parameter sensitivity analyses showed that an increasing number of laterals, lateral length, and horizontal permeability would almost proportionally increase productivity. Well productivity is sensitive to well skin factor and oil viscosity, but not sensitive to the radius of the lateral.
Keywords: radial lateral wells; radial jet drilling; unconventional reservoirs; analytical modeling; well completion (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: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://www.mdpi.com/1996-1073/13/23/6386/pdf (application/pdf)
https://www.mdpi.com/1996-1073/13/23/6386/ (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:13:y:2020:i:23:p:6386-:d:455513
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 ().