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Summary: Aplication of RMN using a probabilistic method into the Echoes inversion
By R. Carmona, J. Hernandez, J. Marcos, C. Minetto, R. Arro.
Introduction
The traditional processing of NMR consists of a sequence of steps, where the last one, lies in taking the echoes that are in the time domain and transform to T2 domain, that in order to make sense of petrophysical to the echoes. The domain change is usually done using a Laplace transform. As a result, we obtain coupled exponential which generates the final T2 function.
The new procedures developed by Baker Hughes Incorporated, change the exponential by probabilitic functions, the result of T2 is more consistent from the mathematical point of view and Geological also visually, is significantly simpler for petrophysical analysis.
The examples are attached, correspond to different sites but there has been emphasis on heavy oil in unconsolidated sands.
Interpretation of gamma probability functions
So far in traditional processing has been working used bins, in this case, has a similar distribution but calculated gamma functions, these are called components, this section will explain how how they present the functions.
The gamma functions have the form of a bell curve with a base in the x-axis logarithmic. Each bell curve, is centralized to a particular time, for example, 0.5 ms, 1 ms, 2 ms ..... Etc. Each curve are called components and are distinguished by means of a number which indicates what time is centralized. For example, Comp1 is the gamma function that is centralized at 0.5 ms, COMP2, was added to 1 ms and so on.
Addittyonaly to the creation of the gamma function, the inteprete has the possibility to change the color for ease association with the particulary event. The sums of all of them generate the spectrum of T2.
The individual area of each component is presented in porosity units, see Figure # 1. In this figure, the first track the total porosity is presented. The second track shows the distribution of gamma functions and the sum total of them, which represents the T2 distribution.
Figure 1
Results. Identification of fluid types
In order to observe the improvements obtained with the new processing is done on this chapter comparisons between traditional and new processing with the use the gamma function develomenp by Baker Hughes Incorporate.
Looking at the record displayed in Figure # 2 shows that in the range of interest exists low resistivities (~ 100 ohmm) compared to the experience in the area, this using traditional logs (GR, Res, DN) can be interpreted in two ways: first, that is fine facies which are affecting the resistive logs, the second could be due to the presence of free water within the formation, in order to optain the answer it is necessary a additionally processing of the data.
Figure 2 
The resonance with the traditional process can be seen that there is a spectrum of T2 distribution with two humps, the first for the oil (if heavy oil) and the second water filter and / or free water in the formation, in order Unlike both, were used (with the traditional processing) to the diffusivity graphics, these graphics are presented in Figure #3 in them shows clearly the difference between the two water, which yields the required argument to say that resisvidad drop is due to free water and not to a change of facies. With the traditional process has been able to differentiate between the two types of water, after making clear that additional processing of information visualization, in the next paragraph presents the results with the new processing.
Figure 3
Figure # 4 shows the new process as a result we can observe the presence of four different types of wavelets, the first two associated with the oil, the latter two into the water, when analyzing the two associated with water in more detail, we have shorter than the corresponding free water formation and the other corresponds to the mud, the identification of these types of fluids is immediate, does not require additional processing such as the diffusivity, this provides a very useful in this process and validity, since they do not have to resort to additional display processing, which are often complex for understanding the interpreter.
Figure 4 
The reason for this time difference is because the mud is invading the formation and thus is located in the largest pore, while that of free water formation is living with the heavy oil and it is found in a less than the poral space, such cases have only been detectable in heavy oil formations.
Viscosity index
Figure # 5a and 5b (top and bottom) presents the results of NMR log processing using the gamma function, you can see at the top that the average hydrogen index is 0.62 in turn is observed only the presence of the first of the component associated with the presence of heavy oil, when analyzing the lower section of the well must be the average hydrogen index changed to 0.74, adicionalmete to this change in the index, there is a change in proportions of the components correlated with oil, this one has the presence of component 2 which had not in the upper interval.
Figure 5a 
Figure 5b 
The relationship between the presence of different components in the area of oil and the viscosity is clear. From the physicochemical point of view, this difference between the presence of the components could be associated with different fractions of oil present, within this last argument is only a hypothesis in which for the moment of realization of this work are working in its demonstration.
Correlation with the image logs
The integration of different logs taken in a well is the key to an interpretation that reflects reality. The stability achieved during the inversion using the gamma function, makes the interpretation of the correlation improves its logs to other, as is the case, with the image logs.
Figure # 6 shows a clay interval within this range, it can be seen as the variation of the reflected component 4 with the yellow colors, the area it increases to a maximum and then begins to drop, into the maximum point can observe the appearance of the component 1, which in this area represents the presence of heavy oil, to make the comparison with the image log can be seen that a number of sandy packets which increase the thickness in the same address the increase in component 4, this increase in thickness is maximum at the point where the signal is heavy oil. This process could identify new hydrocarbon zone with which the traditional processing had not been detected, this creates an added value to the interpretation .
Figure 6 
Figure # 7, shows a comparison between traditional and new processing with respect to image log, this well is extra-heavy oil so the oil signal is located at the early times or components, the first we can observe is that the gamma functions are identified new areas of hydrocarbons, which can not be identified with the traditional method of inversion.
Figure 7 
Conclusions
The new processing generated by Baker Hughes Incorporated improving the mathematics and visual interpretation, this impact in the rapid identification of areas of higher and lowers viscosity, such is the case of heavy oil.
The good correlation between image logs and components indicate that these components may be improving any electro-facies model established in a given field.
The T2 distribution obtained by gamma functions is visually much simpler, which is a great advantage when making interpretations.
R. Carmona, and J. Hernandez, are profesionals with PDVSA and J. Marcos, C. Minetto,and R. Arro are with Baker Hughes. Petroleumworld does not necessarily share these views.
Editor's Note: This paper was prepared for presentation at the International Congress of Conventional and Unconventional Hydrocarbon Resources held in Cartagena , Colombia , February 2008. Also, t his paper was selected for presentation by an ACGGP Technical Committee following review of information contained in an abstract submitted by the author(s).Copyright 2008, ACGGP. Petroleumworld reprint this article in the interest of our readers .
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