Comparison of the Performance of Empirical Models Used for the Prediction of the PVT Properties of Crude Oils of the Niger Delta

Reservoir fluid PVT properties modeling using Adaptive Neuro-Fuzzy Inference Systems

“…In order to develop predictive models, a large data bank from literature as well as unpublished sources was gathered. Literature data were collected from Dokla and Osman (1992), Omar and Todd (1993), Mahmood and Al-Marhoun (1996), Moghadam et al (2011), Obomanu and Okpobiri (1987), De Ghetto and Villa (1994), Ostermann and Owolabi (1983), Gharbi and Elsharkawy (1997), Bello et al (2008). In addition to data gathered from literature two series of 157 and 128 datasets from Iranian oil fields were used for modeling bubble point pressure and OFVF, respectively.…”

Hybrid functional networks for oil reservoir PVT characterisation

“…A total of approximately 1400 data points were available for the simulation. 327 data points were collected from different published papers (Al-Marhoun, 1988;Omar & Todd, 1993;Dokla & Osman, 1992;Bello et al, 2008). The remaining data are unpublished and they are from different sources such as GeoMark Research and Shell Company.…”

Oil Formation Volume Factor Determination Through a Fused Intelligence

“…Hence, gathering of data is an important step in model development using intelligence based model. Dataset which employed in current study for building predictive model for estimation of formation volume factor of crude oil from production data is borrowed from papers available in literature (Al-Marhoun 1988, Bello et al 2008, Dokla and Osman 1990, Mahmood and Al-Marhoun 1996, Moghadam et al 2011, Obomanu and Okpobiri 1987, Omar and Todd 1993. The dataset consists of production data (reservoir temperature, solu-tion gas oil ratio, reservoir oil gravity (API), and dissolved gas relative density) and the corresponding value of FVF.…”