Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Earth science
Reexamination Certificate
2000-05-08
2002-04-02
McElheny, Jr., Donald E. (Department: 2862)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Earth science
Reexamination Certificate
active
06366859
ABSTRACT:
The present invention relates to a method of detecting breaks in logging signals relating to a region of a medium, the logging signals being made up of logs of different kinds recorded for the said region as a function of depth, and the application of this method to a depthwise readjustment of the said logs.
In numerous fields, it is necessary to rapidly correlate two or more curves representing the variations of a first quantity as a function of a second quantity, for purposes of comparison, fitting, etc.
The curves to be compared may be of the same kind, that is to say represent the variations of one and the same first quantity as a function of one and the same second quantity, or of different kinds. They may for example be recordings of one and the same physical phenomenon which are however shifted in time or space, or recordings relating to different physical phenomena or else recordings relating to one and the same physical phenomenon recorded for example by different methods so that their frequency content is different.
The correlations may be performed numerically. The result obtained is generally global and rather unreliable if no constraining assumptions are made regarding the signals, the method then consisting in choosing between several autocorrelation peaks. The correlation can be performed visually, by manually shifting one of the curves with respect to the other along the axis of the second quantity. In this way, optimal similitude is sought over one or more portions of the curve via successive shifts. This method makes it possible to take account of prior knowledge. It is this one which is commonly employed in geophysics for the depthwise or timewise adjusting of seismic horizons or for the correlating of recordings performed in a well and of seismic recordings.
The main drawback of such a method lies in the difficulty in comparing signals of possibly very different shapes, for example if their frequency content is different.
A process for analysing a signal, termed the wavelet analysis process, is known which makes it possible to decompose the said signal as a sum of elementary wavelet functions &PSgr;
a,b
, which each vibrate as sinusoids over a range whose position on an axis is linked to the parameter b and whose width is linked to the parameter a (central frequency), and which are very strongly damped outside this range. The decomposition of a signal with the aid of a family of these wavelets constitutes what is referred to as a “time/frequency” analysis, since the first and most common decompositions were performed on recordings of the variations of a first quantity as a function of time (the second quantity). In this case, the dimension of the parameter b is that of a time and the dimension of the parameter a is the dimension of the inverse of a time, hence of a temporal frequency.
For further information regarding wavelet decomposition or “time/frequency” analyses, reference may be made to the article “L'analyse par ondelette” [Wavelet analysis] by Yves MEYER et al., published in “Pour la Science” of September 1987, to the work “Wavelets” by J. N. COMBES et al. published by Springer-Veriag, or else to the international patent application published under No. WO 92/18941, which documents are incorporated into the present application.
Several types of functions may be used, making it possible to define numerous families of wavelets having different properties. The latter may for example be gaussian, boxcar or triangular functions, real or complex functions, which may or may not be mutually orthogonal. Reference will be made to the above-cited article to ascertain the constraints applicable to these various functions and to others in order to generate wavelet families.
For a specified family of wavelets &PSgr;
a,b
, the “wavelet transform” in two dimensions z and x, which is associated with a recording s(z) along the z axis, is defined as the sequence of coefficients C
a,b
which each correspond to the integral of the product of the recording s(z) to be analysed times the elementary analysis wavelet &PSgr;
a,b
according to the values of b along the z axis and the values of a along an x axis. In the case where complex wavelets have been chosen to perform the time/frequency analysis of a recording or of a signal, it becomes possible to define the real part, the imaginary part, the modulus or else the phase of the wavelet transform. The coefficients C
a,b
are calculated through the well known formula:
C
a,b
=∫
−oo
+oo
S(z)
a,b
(z)dz
Methods and devices for identifying geological structures using wavelet transforms are described in particular in patents U.S. Pat. No. 5,673,191, U.S. Pat. No. 5,740,036 and U.S. Pat. No. 5,757,309 and in the article entitled “Detection of non stationarites in geological time series: wavelet transform of chaotic and cyclic sequences”, by Andreas PROKOPH et al, published in Computers and Geosciences, Vol. 22, N° 10, pages 1097-1108, 1996.
However, these latter documents relate either to magnetic and gravitational measurements for distinguishing between relatively deep geological structures and shallow structures, or to means for simulating the succession of structures.
The present invention relates to a method of detecting breaks in logging signals, which uses a wavelet analysis of the said signals.
It is known that the analysis of the logging signals obtained with the aid of well known devices makes it possible to determine the mineralogy, the texture, the type of porous lattice and the fluid content of the formations through which boreholes are drilled. The depthwise alterations in the signals reflect the alterations in the properties of the formations and make it possible to chart their structural and diagenetic sedimentary history.
Within the logging signals it is possible to distinguish breaks which correspond to significant modifications of the nature of the formations which occur over a small depth interval.
Electrofaciological beds may be characterized on the basic of the breaks plotted on at least one of the channels of the logging signal. Inside a bed, each channel of the logging signal shows a continuous variation, on a given depth resolution scale. The noteworthy breaks are used by the geologist for lithostratigraphic correlation purposes. In certain cases, chronostratigraphic correlations are possible by performing an interpretation on the basis of a conceptual model of the alterations of the sedimentary deposits.
Specialists performing the analysis of the logging signals use the noteworthy breaks, in the first step of the interpretation, for the depthwise readjustment of the various signals recorded by the sensors of the logging device which are not all located in front of the same formation at the same time. On either side of the breaks, the logging signal suffers from a shoulder effect over an interval which depends on the resolution of the logging devices and on the contrast of the characteristic logging responses of the formations. This shoulder effect is a source of errors and uncertainty in the interpretations.
The present-day processes for interpreting logging signals are based on processing each sample of the logging signal independently of the samples lying above and below the processed sample, the concept of depth not being involved. Accordingly, the information carried by the alterations of the signal with depth is not taken into account. In order for this information to be taken into account, it is necessary to define breaks over the logging signal and alterations inside the breaks.
The determination of breaks is currently performed manually and requires an experienced operator. The result is both subjective and difficult to reproduce identically. However, these breaks which correspond to the limits of beds or of formations are necessary for depthwise readjustment.
Depthwise readjustment is a fundamental step in all interpretation of logs, since it consists in resetting to the same depth measurements performed by the various sensors of the logging devices, which do n
Rabiller Philippe
Robail Frédéric
Elf Exploration Production
McElheny Jr. Donald E.
Ostrolenk Faber Gerb & Soffen, LLP
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