The main purpose of this study is to estimate hydrocarbon potentialities Yamama Formation (Valanginian–Early Hauterivian) by using assessment technique links up between gamma ray spectrometry logs and other conventional open hole for determining the petrophysical properties units in Subba oil-field oil water contact as well. Lower (YB); considered reservoir unit, aptly composed shallow high dep...

We combine a new pore-scale model with a reservoir simulation algorithm to predict gas production in gas-bearing shales. It includes an iterative verification method of surface mass balance to ensure real-time desorption-adsorption equilibrium with gas production. The pore-scale model quantifies macroscopic petrophysical properties of formations using an algorithm of gas transport in porous med...

Determination of Geostatistical Parameters Using Well Test Data — In this paper we describe a new method to obtain estimations of the geostatistical parameters (GPs) such as the correlation length, lc and the permeability variance, σln from well test data. In practical studies, the GPs are estimated using geological and petrophysical data, but often, these data are too scarce to give precise re...

A large-scale data set including time-lapse (4D) elastic attributes and electrical resistivity is generated with the purpose of testing algorithms for reservoir modeling, reservoir characterization, production forecasting, and especially joint time-lapse monitoring using seismic as well as electromagnetic data. The Stanford VI reservoir, which was originally created by Castro et al. (2005), is ...

Porosity is one of the key parameters associated with oil reservoirs. Determination of this petrophysical parameter is an essential step in reservoir characterization. Among different linear and nonlinear prediction tools such as multi-regression and polynomial curve fitting, artificial neural network has gained the attention of researchers over the past years. In the present study, two-dimensi...

2 1. Research aims 3 2. Introduction 3 3. Materials and methods 5 3.1. Origin of samples 5 3.2. Methods 5 4. Experimental results 7 4.1. Petrographic description 7 4.2. Main petrophysical properties 7 4.3. Overall mineralogy 8 4.4. Clay minerals quantification 9 4.5. Hydromechanical behavior 10 5. Discussion 11 5.1. Identification and origin of the swelling layers 11 5.2. Influence of swelling ...

The prediction of lithology is necessary in all areas of petroleum engineering. This means that to design a project in any branch of petroleum engineering, the lithology must be well known. Support vector machines (SVM’s) use an analytical approach to classification based on statistical learning theory, the principles of structural risk minimization, and empirical risk minimization. In this res...