The objective of this work is to implement a pseudo-forward equation which is called PFE to transform data (similarity attribute) to model parameters (porosity) in a gas reservoir in the F3 block of North Sea. This equation which is an experimental model has unknown constants in its structure; hence, a least square solution is applied to find the best constants. The results derived from solved equations show that the errors on measured data are mapped into the errors of estimated constants; hence, Tikhonov regularization is used to improve the estimated parameters. The results are compared with a conventional method such as cross plotting between acoustic impedance and porosity values to validate the PFE model. When the testing dataset in sand units was used, the correlation coefficient between two variables (actual and predicted values) was obtained as 0.720 and 0.476 for PFE model and cross-plotting analysis, respectively. Therefore, the testing dataset validates relatively well the PFE optimized by Tikhonov regularization in sand units of a gas reservoir. The obtained results indicate that PFE could provide initial information about sandstone reservoirs. It could estimate reservoir porosity distribution approximately and it highlights bright spots and fault structures such as gas chimneys and salt edges.

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The present research focuses to investigate the relationship between spectral and chemical characteristics of water samples in Darrehzar mine. In order to reach this aim the chemical characteristics of water were measured through pH, electrical conductivity (EC) and inductively coupled plasma mass spectrometry (ICP-MS) analysis. Furthermore, the visible near infrared (VNIR) and shortwave infrared (SWIR) spectra of water samples were measured by Analytical Spectral Devices (ASD) FieldSpec3 spectroradiometer and the relationships between spectral and chemical characteristics of water samples were calculated. Results of the pH and EC measurements showed that water with high acidity and EC values which indicates presence of acid drainage was located inside the mine. High concentration of copper, sulfur and iron at the samples could be related to copper mineralization and association with acid mine drainage. Results of spectroscopy revealed that second absorption feature (AF2) magnitude correlated significantly with pH (−0.599), EC (0.611) (p < 0.1) and total trace elements plus sulfur (0.822) (p < 0.05). The significant correlation of the AF2 magnitude with concentrations of S (0.854), Pb (0.914), Ni (0.836), Mn (0.834), Co (0.848) and AF3 with concentration of Fe (0.886) confirm that absorption feature magnitude increases by increasing metals concentrations in water.