S Tabasi; A KamkarRouhani; M.M Khorasani
Abstract
Archie’s equation, which is the most fundamental equation for water saturation calculation,consists of three factors: Cementation factor (m), saturation exponent (n) and tortuosity (a). Cementation factor is a function of the shape of pores. Hence, the study of pore type is important in determining ...
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Archie’s equation, which is the most fundamental equation for water saturation calculation,consists of three factors: Cementation factor (m), saturation exponent (n) and tortuosity (a). Cementation factor is a function of the shape of pores. Hence, the study of pore type is important in determining the Archie’s coefficients. In order to achieve more precise and reliable results in Archie’s coefficient determination and then water saturation accurately, the rocks must be rated based on texture and porosity type, where the coefficients should be constrained for each class. In this paper, fractal method is used to rate the resistivity log data and calculate Archie’s coefficient in an exploration well of a hydrocarbon reservoir in southwest of Iran. The results show three different zones based on porosity type and texture of the rocks. Then the Genetic algorithm method is used to calculate the Archie’s coefficients in each of the zones separately. The results show that this method is able to consider the complex behavior of each of the coefficients in the calculations.
M. A. Oladzad Abbas Abadi; B. Movahed
Abstract
Hydrocarbon potential Evaluation of formations by using ∆logR method (a method based on separation of well logging of porosity DT/CN./RHOB) and resistivity well logging (Rt). This method has been today applied as an appropriate method in many of famous wells of the world. The beginning of these methods ...
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Hydrocarbon potential Evaluation of formations by using ∆logR method (a method based on separation of well logging of porosity DT/CN./RHOB) and resistivity well logging (Rt). This method has been today applied as an appropriate method in many of famous wells of the world. The beginning of these methods drew attention of many researchers in 1980. It had organic matters on the well logging based on the influences of layers containing organic matters. Passey et al. (1990) provided away for predicting of rich of organic material in source rock that have a high accuracy and potential for studying extensive rang of maturity condition. The basis of this method is overlapping porosity well logging (sonic, neutron, density) scaled on the resistivity well logging and determining the degree of separation between these two loges and calculation of total organic carbon TOC and S2. Using this method we can gain appropriate relative evaluation of formations without preparing sample during times of exploration. In this study, the areas which have rich organic matter of Gadvan formation in the SP-A well located in the South Pars Area have been deter mind with use of ∆logR way and for SP-A well, yielding results of this studies was compared with data relating to Rock – Eval Pyrolysis analysis of core samples and was observed good correlation.
M. Paryab
Abstract
Hydrocarbon source rocks, the subject of various analyses and investigations, are well appreciated because of their capacity for oil generation. In the present study, attempts were made to evaluate source rock using a leap cost analytical method. For this purpose, some samples from these formations were ...
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Hydrocarbon source rocks, the subject of various analyses and investigations, are well appreciated because of their capacity for oil generation. In the present study, attempts were made to evaluate source rock using a leap cost analytical method. For this purpose, some samples from these formations were analyzed by Rock- Eval. CO2 generated from these samples at 350ºС are calculated as mgHy/gr rock or Kg Hy/Ton rock. As this method requires more time and is relatively expensive, we offered a new method in which by calibration of data, obtained from analyzed samples, the result could be attributed to the whole interval of a formation. By calculation of S2, Tmax and TOC of analyzed samples collected from wells A and B for both Pabdeh and Gurpi formations in accordance with ∆LogR method, rescaling of Resistivity-sonic logs, Resistivity-Density logs and Resistivity-Neutron logs, TOC content of these formations were estimated. Comparison between these data and data obtained from direct sample measurements in lab and extrapolation of an equation that relates these data to S2 and TOC of sample analysis, TOC and S2 content of whole intervals of these formations were calculated through ∆LogR method. Then hydrocarbon generation potential of the Pabdeh and Gurpi formations were finally evaluated. These data were processed in a neural network method with forward back propagation capability designed as try and error structure within Matlab software. Final results are in good agreement with those data obtained from direct measurements.
