Evaluates A PVT Correlation to Estimate Dead Oil Viscosity for Libyan Crudes Using 104 Samples from Different Reservoirs

  • Mohammed Alsharif Emhemmed Massoud phd student at china university of petroleum
  • Mohammed A. Samba Phd candidate at china university of petroleum Beijing , China
  • Li Yiqiang Member of petroleum engineering staff at china university of petroleum Beijing, China
  • Wannees A. Alkhyyali Engineer at oil and gas engineering department, Sebha University, Libya
  • Yousef A. Altaher Engineer at oil and gas engineering department, Sebha University, Libya
  • Fiki Hidaya Member at Petroleum Engineering Staff, Faculty of Engineering, Universitas Islam Riau, Pekanbaru, Indonesia

Abstract

Viscosity is defined as the resistance of the fluid to flow. It plays a very significant role in most oil and gas engineering applications, including production stages and reservoir simulation. In general, the dead oil viscosity is used in most applications. This study evaluates a PVT correlation to estimate dead oil viscosity for Libyan crudes using 104 samples from different reservoirs. A new mathematical and artificial neural network (ANN) dead oil viscosity correlations were developed for Libyan crudes and compared with renowned dead oil viscosity correlations. The evaluation in this study has been done by statistical and graphical error analysis. An ANN model has been proven to be a useful tool for predicting where the ANN model has given the best result with low error AAD was 14.40509 % and

Published
2021-11-03
Section
Petroleum Engineering