CN102053264A - Oil gas forecasting method - Google Patents

Abstract

The invention provides an oil gas forecasting method which comprises the steps of: 1, carrying out wavelet transform on longitudinal wave signals at a plurality of points on a region to obtain a wavelet transform coefficient of each longitudinal wave signal; 2, aiming at each longitudinal wave signal, comparing the wavelet transform coefficients of the longitudinal wave signals under different scale parameters theta, determining the corresponding scale parameter theta best when the wavelet transform coefficient is maximum; 3, aiming at each longitudinal wave signal, under the determined scale parameter theta best of each longitudinal wave signal, calculating the main frequency and/or quality factor of each longitudinal wave signal, wherein the quality factor is a parameter for reflecting the shake energy loss degree of the longitudinal wave signal; and 4, forecasting the potential region of oil gas distribution according to the calculated main frequency and/or quality factors of the longitudinal wave signals. In the invention, by using better time domain and frequency domain local change characteristics of a wavelet function, the main frequency and/or quality factors of the longitudinal wave signals under the best scale parameters can be figured out, and the main frequency and/or quality factors can accurately reflect the attenuation characteristics of the longitudinal wave signals, thereby being capable of accurately forecasting the potential region of the oil gas distribution.

Description

A kind of petroleum-gas prediction method

Technical field

The present invention relates to the geophysical exploration technology field, and relate in particular to a kind of petroleum-gas prediction method, be applicable to the space distribution of prediction oil, rock gas.

Background technology

The seventies in 20th century, the geophysicist finds: hydro carbons has special response to the high frequency composition, i.e. high frequency heavy losses, and dominant frequency obviously reduces.The two-phase media theory confirms that also reservoir of oil and gas is made up of solid skeletal and pore fluid, and the viscosity of loose skeleton and pore fluid will cause the decay of compressional wave.Biot (1961) and Wyllie (1961) have studied the characteristic of compressional wave decay, and the decay in the skeleton is caused by solid friction on the one hand, and is relevant with frequency on the other hand; And the decay in the pore fluid is caused by frequency fully.

How to utilize the frequency and the attenuation by absorption attribute of compressional wave to describe the response characteristic of pore fluid exactly, and reach the purpose of petroleum-gas prediction?

In the past, people often adopt the Fourier transform method to calculate attenuation by absorption attributes such as the quality factor of compressional wave signal, absorption coefficient, plan absorption coefficient, logarithmic decrement in frequency field, and the response characteristic of portraying reservoir of oil and gas with the variation of these attributes.Yet, because Fourier transform is fit to the analysis of stationary signal very much, there is limitation and handle non-stationary signal (time varying signal), when mainly existing window width can't hold (" Fourier transform is to consider a unlimited time period; and this and wes' actual life differs greatly ", Gabor, 1946), local characteristic very poor, be difficult to use in problems such as micro-analysis.Thereby for the compressional wave signal of non-stationary, the dominant frequency of the compressional wave signal that calculates based on Fourier transform and the precision of absorption properties etc. will be interfered, and this will directly influence the result of petroleum-gas prediction.

Summary of the invention

Can arrive interference less in order to solve dominant frequency and the absorption properties of utilizing the Fourier converter technique in frequency field, to calculate the compressional wave signal in the prior art, thereby influence petroleum-gas prediction result's defective, the special proposition of the application is a kind of can accurately determine the dominant frequency of compressional wave signal and/or the new petroleum-gas prediction method of absorption properties.

Petroleum-gas prediction method provided by the invention comprises: 1) the compressional wave signal to the place, a plurality of place in the zone carries out wavelet transformation, obtains the wavelet conversion coefficient of each compressional wave signal; 2) at each compressional wave signal, the wavelet conversion coefficient of this compressional wave signal under different scale parameter σ relatively, pairing scale parameter σ when determining that wavelet conversion coefficient is maximum _Best3) at each compressional wave signal, at the scale parameter σ of determined this compressional wave signal _BestDown, calculate the dominant frequency and/or the quality factor of this compressional wave signal, this quality factor is the parameter of this compressional wave signal vibration energy extent of deterioration of reflection; And 4) according to the dominant frequency and/or the quality factor of a plurality of compressional wave signals that calculated, the range of profitability that predicting oil distributes.

The present invention is by utilizing good time domain of wavelet function and frequency field localized variation characteristic, adopt means multiple dimensioned, multiresolution to calculate the dominant frequency and/or the quality factor of compressional wave signal at time-frequency domain, thereby can draw compressional wave signal dominant frequency and/or quality factor under the different scale parameter, and compressional wave the signal dominant frequency under the pairing scale parameter (referred to herein as the best scale parameter) and/or quality factor when wavelet conversion coefficient is maximum are the decay characteristics that can most accurately reflect the compressional wave signal.Utilize determined dominant frequency and/or quality factor and gassiness response characteristic, just can predict the range of profitability of hydrocarbon occurrence exactly.

Description of drawings

Fig. 1 is the process flow diagram of petroleum-gas prediction method of the present invention.

Embodiment

Describe the present invention in detail below with reference to accompanying drawing.

As shown in Figure 1, the invention provides a kind of petroleum-gas prediction method, this method comprises: 1) the compressional wave signal to the place, a plurality of place in the zone carries out wavelet transformation, obtains the wavelet conversion coefficient of each compressional wave signal; 2) at each compressional wave signal, the wavelet conversion coefficient of this compressional wave signal under different scale parameter σ relatively, pairing scale parameter σ when determining that wavelet conversion coefficient is maximum _Best3) at each compressional wave signal, at the scale parameter σ of determined this compressional wave signal _BestDown, calculate the dominant frequency and/or the quality factor of this compressional wave signal, this quality factor is the parameter of this compressional wave signal vibration energy extent of deterioration of reflection; And 4) according to the dominant frequency and/or the quality factor of a plurality of compressional wave signals that calculated, the range of profitability that predicting oil distributes.

Wherein, described zone can be explored needs according to reality and be chosen, and for example can be 200-600 square kilometre.Described a plurality of place is preferably and is uniformly distributed in the described zone, certainly according to actual environment, carries out suitable adjustment, and the present invention is not limited to this.

Wherein, the compressional wave signal can be represented by compressional wave amplitude propagation equation:

$A(\mathrm{\ω},t)=A(\mathrm{\ω},0)\exp [\mathrm{i\ωt}-\frac{\mathrm{\ωt}}{2Q}]---\left(1\right)$

In equation (1), (ω t) is the t amplitude of compressional wave constantly to A; A (ω, 0) is the amplitude of zero moment compressional wave; ω is the angular frequency of compressional wave signal; Q is the parameter of reflection compressional wave signal vibration energy extent of deterioration.

Wherein, described step 2) comprising: according to the wavelet conversion coefficient F of following formula (2) calculating corresponding to different scale parameter σ _A(σ, τ),

$F_A(\mathrm{\σ},\mathrm{\τ})={\∫}_{-\∞}^{\∞}A(\mathrm{\ω},t)\frac{1}{\sqrt{\mathrm{\σ}}}{\mathrm{\ψ}}^{*}\left(\frac{t-\mathrm{\τ}}{\mathrm{\σ}}\right)\mathrm{dt}---\left(2\right)$

Wherein, F _A(σ τ) is wavelet conversion coefficient, A (ω is the t amplitude of compressional wave constantly t), and σ is a scale parameter, and τ is the time displacement parameter, the time span of expression compressional wave signal,

It is Morlet wavelet function

Conjugate complex number; And

A plurality of from what calculate | F _A(σ, τ) | in determine maximum wavelet conversion coefficient | F _A(σ, τ) | _MaxAnd pairing scale parameter σ _Best

In described Morlet wavelet function, i is an imaginary unit; E is the truth of a matter of natural logarithm function; ω ₀Be given initial angle frequency, this initial angle frequency can be any arithmetic number, generally gets the 5-200 hertz; C is any arithmetic number, acts on Gauss's part of wavelet function, and with the form of modulating wave, to obtain the purpose of best seismic wavelet, when the c value was big more, waveform compression was severe more, secondary lobe reduces, wavelet narrows down.Generally speaking, the span of c is 0-1.

Wherein, described different scale parameter σ can be any arithmetic number, and promptly wavelet can be compressed or stretch infinite times.Generally speaking, described scale parameter σ can comprise and is selected from a plurality of constant values except that 0 among the 0-10000.

In above-mentioned equation (2), different σ values can obtain different wavelet conversion coefficients | F _A(σ, τ) |, wavelet conversion coefficient | F _A(σ, τ) | reflected A (ω, t) and the degree of correlation between the Morlet wavelet function, promptly | F _A(σ, τ) | big more, then represent A (ω, t) and the correlativity between the Morlet wavelet function good more.Thus, can analyze the scale feature of compressional wave signal, realize the multiscale analysis of compressional wave signal by the wavelet conversion coefficient under the different scale parameter.Therefore, select maximum wavelet conversion coefficient | F _A(σ, τ) | _MaxPairing scale parameter σ _BestHelp calculating exactly the dominant frequency and/or the quality factor of compressional wave signal.

The dominant frequency of described compressional wave signal can be calculated by following formula:

$f=\frac{1.875}{{\mathrm{\σ}}_{\mathrm{best}}\mathrm{\Δt}}---\left(3\right)$

Wherein, f is the dominant frequency of compressional wave signal; Δ t is a compressional wave signals sampling rate, and this sampling rate is generally 1-10ms.

The quality factor of described compressional wave signal is calculated by following formula:

$Q=\frac{0.5\sqrt{{\left(\mathrm{\σ}{\mathrm{\ω}}_0\right)}^2+{\left(\mathrm{\σc}\right)}^2{[\ln \mathrm{\σ}+\ln \sqrt{\mathrm{\π}}+\ln |F_A(\mathrm{\σ},\mathrm{\τ})\left|\right]+(t-\mathrm{\τ})]}^2{c}^4}-0.5\mathrm{\σ}{\mathrm{\ω}}_0}{{\mathrm{\σ}}^2\{\ln \mathrm{\σ}+\ln \sqrt{\mathrm{\π}}+\ln |F_A(\mathrm{\σ},\mathrm{\τ})\left|\right\}+{\left[c(t-\mathrm{\τ})\right]}^2}t---\left(4\right)$

Wherein, Q is a quality factor, the attenuation by absorption that factors such as the interior friction between the reflection rock particles, pore fluid viscous effect, pore texture cause compressional wave to occur, be the direct response of stratal configuration, rock type, fluid properties, rerum natura variation, thereby it can play a significant role in petroleum-gas prediction.In formula (4), Q is with σ, F _A(σ τ), t is the function of variable, utilizes these variablees can calculate Q value the most accurately, thereby has avoided the precision influence that utilizes the Fourier transformation calculations to bring in the background technology method, do not need to calculate again yet A (ω, t).Therefore, the Q value that calculates according to this formula has degree of accuracy height, reflection oil gas information advantage accurately.

Repeat above-mentioned steps, can obtain the dominant frequency and/or the quality factor of a plurality of compressional wave signals, calculate the mean value of the dominant frequency and/or the quality factor of these a plurality of compressional wave signals then, can obtain dominant frequency mean value f _aAnd/or quality factor mean value Q _a

Wherein, can select one of the dominant frequency of described compressional wave signal and quality factor (promptly as predicting oil distribution range of profitability, be distributed with the very high zone of possibility of oil gas) foundation, because when compressional wave signal during through hydrocarbon occurrence regional, can cause the dominant frequency and the quality factor of compressional wave signal to decay, therefore, with the dominant frequency f and the described dominant frequency mean value f of current compressional wave signal _aCompare, as f＜f _aThe time, show that the dominant frequency of current compressional wave signal will be lower than average dominant frequency, can judge that thus current compressional wave signal has probably passed through the zone that has hydrocarbon occurrence, has caused the dominant frequency decay.So, as f＜f _aThe time, then judge current compressional wave signal by way of the zone be the range of profitability of hydrocarbon occurrence.In like manner, as Q＜Q _aThe time, judge that then the zone of current compressional wave signal institute approach is the range of profitability of hydrocarbon occurrence.

Preferably, can promptly satisfy f＜f simultaneously with the dominant frequency of compressional wave signal and quality factor simultaneously as the foundation of predicting oil distribution range of profitability _aAnd Q＜Q _aThe time, the regional determination of compressional wave signal institute approach is the range of profitability of hydrocarbon occurrence before just will being somebody's turn to do.Can improve the degree of accuracy of prediction like this.

The present invention is by utilizing good time domain of wavelet function and frequency field localized variation characteristic, can calculate dominant frequency and/or the quality factor of compressional wave signal under the best scale parameter, this dominant frequency and/or quality factor can reflect the decay characteristics of compressional wave signal exactly, thereby can predict the range of profitability of hydrocarbon occurrence exactly.

Though the present invention is disclosed by the foregoing description, yet the foregoing description is not to be used to limit the present invention, and any the technical staff in the technical field of the invention without departing from the spirit and scope of the present invention, should do various changes and modification.Therefore protection scope of the present invention should be as the criterion with the scope that appended claims was defined.

Claims (8)

1. petroleum-gas prediction method, this method comprises:

1) the compressional wave signal to the place, a plurality of place in the zone carries out wavelet transformation, obtains the wavelet conversion coefficient of each compressional wave signal;

2) at each compressional wave signal, the wavelet conversion coefficient of this compressional wave signal under different scale parameter σ relatively, pairing scale parameter σ when determining that wavelet conversion coefficient is maximum _Best

3) at each compressional wave signal, at the scale parameter σ of determined this compressional wave signal _BestDown, calculate the dominant frequency and/or the quality factor of this compressional wave signal, this quality factor is the parameter of this compressional wave signal vibration energy extent of deterioration of reflection; And

4) according to the dominant frequency and/or the quality factor of a plurality of compressional wave signals that calculated, the range of profitability that predicting oil distributes.

2. method according to claim 1, wherein,

According to the wavelet conversion coefficient F of following formula calculating corresponding to different scale parameter σ _A(σ, τ),

$F_A(\mathrm{\σ},\mathrm{\τ})={\∫}_{-\∞}^{\∞}A(\mathrm{\ω},t)\frac{1}{\sqrt{\mathrm{\σ}}}{\mathrm{\ψ}}^{*}\left(\frac{t-\mathrm{\τ}}{\mathrm{\σ}}\right)\mathrm{dt},$

Wherein, F _A(σ τ) is wavelet conversion coefficient, A (ω is the t amplitude of compressional wave constantly t), and σ is a scale parameter, and τ is the time displacement parameter, It is Morlet wavelet function

Conjugate complex number, in described Morlet wavelet function, i is an imaginary unit, e is the truth of a matter of natural logarithm function, ω ₀Be the initial angle frequency, c is a constant.

3. method according to claim 2, wherein, described different scale parameter σ comprises and is selected from a plurality of constant values except that 0 among the 0-10000.

4. method according to claim 2, wherein, c is the arbitrary constant value between the 0-1.

5. method according to claim 2, wherein, ω ₀Be the 5-200 hertz.

6. method according to claim 2, wherein, in described step 3), the dominant frequency of compressional wave signal is calculated by following formula:

$f=\frac{1.875}{{\mathrm{\σ}}_{\mathrm{best}}\mathrm{\Δt}}$

Wherein, f is the dominant frequency of compressional wave signal; Δ t is a compressional wave signals sampling rate;

The quality factor of described compressional wave signal is calculated by following formula:

$Q=\frac{0.5\sqrt{{\left(\mathrm{\σ}{\mathrm{\ω}}_0\right)}^2+{\left(\mathrm{\σc}\right)}^2{[\ln \mathrm{\σ}+\ln \sqrt{\mathrm{\π}}+\ln |F_A(\mathrm{\σ},\mathrm{\τ})\left|\right]+(t-\mathrm{\τ})]}^2{c}^4}-0.5\mathrm{\σ}{\mathrm{\ω}}_0}{{\mathrm{\σ}}^2\{\ln \mathrm{\σ}+\ln \sqrt{\mathrm{\π}}+\ln |F_A(\mathrm{\σ},\mathrm{\τ})\left|\right\}+{\left[c(t-\mathrm{\τ})\right]}^2}t$

Wherein, Q is a quality factor.

7. according to the described method of each claim among the claim 1-6, wherein, described step 4) comprises:

The dominant frequency of current compressional wave signal or quality factor and described dominant frequency mean value or quality factor mean value are compared, when the dominant frequency of current compressional wave signal less than dominant frequency mean value or quality factor during less than quality factor mean value, judge current compressional wave signal by way of the zone be the range of profitability of hydrocarbon occurrence.

8. according to the described method of each claim among the claim 1-6, wherein, described step 4) comprises the dominant frequency of current compressional wave signal and quality factor is compared with dominant frequency mean value and quality factor mean value respectively, when the dominant frequency of current compressional wave signal less than dominant frequency mean value and quality factor during less than quality factor mean value, judge current compressional wave signal by way of the zone be the range of profitability of hydrocarbon occurrence.