CN105223618A - Veneer microfacies inversion method and device - Google Patents

Abstract

The invention provides a kind of veneer microfacies inversion method and device, the method comprises: in work area, select many mouthfuls of wells, determines the reservoir thickness of the zone of interest of every mouthful of well in described many mouthfuls of wells, response frequency, response amplitude and sedimentary micro type; Set up the relation between sedimentary micro and reservoir thickness, the relation between reservoir thickness and response frequency, the relation between reservoir thickness and response amplitude, the relation between sedimentary micro and response frequency, the relation between sedimentary micro and response amplitude, and select three fusion frequencies and each self-corresponding sedimentary micro according to the relation determined; According to each self-corresponding sedimentary micro of described three fusion frequencies and each self-corresponding fusion amplitude range, RGB fusion is carried out to described three fusion frequencies, obtain veneer microfacies inversion result.The invention solves in prior art three frequencies cannot effectively determining to merge attribute in RGB integration technology, and cause predicting the inaccurate technical matters of the sedimentary micro obtained.

Description

Veneer microfacies inversion method and device

Technical field

The present invention relates to oil exploration technology field, particularly a kind of veneer microfacies inversion method and device.

Background technology

The object of seismic data inverting is, by utilizing aboveground low frequency and high-frequency information to mend wide by the seismic data frequency band range of few for scarce low frequency high frequency, and then improves seismic data to the resolution characteristic of geological information.

Since 3-D seismics prospecting techniques is born, seismic properties has played important effect in the research of prediction sedimentary facies.Along with deepening continuously to lithologic deposit research, the research of thin layer becomes the focus of people's concern.Partyka in 1999 etc. utilize Spectral Decomposition Technique, and by the contrast of cutting into slices to the frequency division compared with low-frequency range and higher frequency band, show that sand body grows thicker wider river course preferentially in comparatively low-frequency range imaging, sand body grows thinner river course in higher frequency range imaging.Calendar year 2001 Marfurt and Kirlin utilizes RGB integration technology to predict the thin and thick regularity of distribution of river channel sand.Bahorich in 2002 etc. utilize RGB integration technology to predict the deposition phasor of marine site, West Africa composite natral dike and river channel sand equally, and the development of RGB integration technology makes geophysical techniques play vital role in the sedimentary facies prediction of thin layer.

For RGB integration technology, need effectively to determine to merge three frequencies in attribute, sedimentary micro just can be made to predict more rationally if any more adequately choosing these three frequencies, not yet proposing effective solution at present.

Summary of the invention

Embodiments provide a kind of veneer microfacies inversion method, to reach the object of Accurate Prediction sedimentary micro, the method comprises:

In work area, select many mouthfuls of wells, determine the reservoir thickness of the zone of interest of every mouthful of well in described many mouthfuls of wells;

In described many mouthfuls of wells, the reservoir lower bound of the zone of interest of every mouthful of well is as assay surface, and in seismic section, upwards first schedule time, downward second schedule time carry out tuning analysis as analysis window, to determine the response frequency of the zone of interest of every mouthful of well;

In single-frequency volume data, extract peak swing value along the zone of interest of every mouthful of well in described many mouthfuls of wells, read response amplitude according to described peak swing value at the correspondence position of every mouthful of well;

Determine the sedimentary micro type of every mouthful of well at well point place in described many mouthfuls of wells;

According to the sedimentary micro type determined and the described reservoir thickness determined, set up the relation between sedimentary micro and reservoir thickness;

According to the reservoir thickness determined and the response frequency determined, set up the relation between reservoir thickness and response frequency;

According to the reservoir thickness determined and the response amplitude determined, set up the relation between reservoir thickness and response amplitude;

According to the sedimentary micro type determined and the response frequency determined, set up the relation between sedimentary micro and response frequency;

According to the sedimentary micro type determined and the response amplitude determined, set up the relation between sedimentary micro and response amplitude;

Three fusion frequencies and each self-corresponding sedimentary micro is selected according to the relation between described sedimentary micro and reservoir thickness, the relation between described sedimentary micro and response frequency, the relation between sedimentary micro and response amplitude and the relation between described reservoir thickness and response frequency;

Three each self-corresponding fusion amplitude ranges of fusion frequency are determined according to the relation between described reservoir thickness and response frequency;

According to each self-corresponding sedimentary micro of described three fusion frequencies and each self-corresponding fusion amplitude range, RGB fusion is carried out to described three fusion frequencies, obtain veneer microfacies inversion result.

In one embodiment, in described many mouthfuls of wells the zone of interest of every mouthful of well reservoir at the bottom of boundary as assay surface, in seismic section, upwards first schedule time, downward second schedule time carry out tuning analysis as analysis window, to determine the response frequency of the zone of interest of every mouthful of well, comprising:

In described many mouthfuls of wells the zone of interest of every mouthful of well reservoir at the bottom of boundary as assay surface, upwards first schedule time, downward second schedule time in seismic section, Short Time Fourier Transform is carried out to geological data, obtains frequency tuning range;

Using described frequency tuning range as constraint, adopt maximum entropy method (MEM) to process described geological data, determine the response frequency of the zone of interest of every mouthful of well.

In one embodiment, following formula is adopted to carry out Short Time Fourier Transform:

$s(f,\mathrm{\τ})=\frac{1}{\sqrt{2\mathrm{\π}}}\∫s\left(t\right)w(t-\mathrm{\τ})e^{-j2\mathrm{\π}ft}dt$

Wherein, s (t) represents geological data, and w (t-τ) is expressed as window letter, and f represents response frequency, and t represents the time.

In one embodiment, adopt maximum entropy method (MEM) to process described geological data, determine the response frequency of the zone of interest of every mouthful of well, comprising:

By following K rank autoregression difference equation simulated earthquake data, and obtain autoregressive coefficient and the variance of described K rank autoregression difference equation:

$x\left(t\right)-\underset{k=1}{\overset{K}{\Σ}}{\mathrm{\α}}_k{x}_{t-k}=e\left(t\right)$

Wherein, x (t) represents the seismic trace of geological data; α _krepresent autoregressive coefficient, and | α _k| <1, k=1,2 ..., e (t) represents predicated error, is a white noise sequence, K=2N/ln (2N), and wherein, N represents the length of seismologic record;

According to described autoregressive coefficient and described variance, by following formulae discovery power spectrum:

$P\left(f\right)=\frac{{{\mathrm{\&delta;}}_k}^2}{{\left|1-\underset{m=1}{\overset{K}{\&Sigma;}}{\mathrm{\&alpha;}}_{mm}{e}^{-j2\mathrm{\&pi;}fm\mathrm{\&Delta;}t}\right|}^2}$

Wherein, P (f) represents estimated power spectrum, represent the variance of e (t), α _mmrepresent autoregressive coefficient, f represents response frequency, and t represents the time;

The response frequency of the zone of interest of every mouthful of well is determined from described power spectrum.

In one embodiment, described single-frequency volume data is asked for according to following formula:

For arbitrary function f (t) ∈ L ²(R), its continuous wavelet transform is:

$W_{\mathrm{\&psi;}}f(a,b)=\frac{1}{\sqrt{\left|a\right|}}{\&Integral;}_{-\mathrm{\&infin;}}^{+\mathrm{\&infin;}}f\left(t\right)\mathrm{\&psi;}*\left(\frac{t-b}{a}\right)dt$

Wherein, W _ψrepresent signal time-size distribution, a represents scale factor, and b represents shift factor, and ψ represents a morther wavelet, and f represents response frequency, and t represents the time, L ²(R) quadractically integrable function space is represented.

In one embodiment, it is characterized in that, according to each self-corresponding sedimentary micro of described three fusion frequencies and each self-corresponding fusion amplitude range, RGB fusion carried out to described three fusion frequencies, obtain veneer microfacies inversion result, comprising:

The each self-corresponding fusion amplitude range of described three fusion frequencies is normalized;

By the fusion frequency after normalized and each self-corresponding sedimentary micro of described three fusion frequencies, RGB fusion is carried out to described three fusion frequencies, obtains veneer microfacies inversion result.

In one embodiment, according to following formula, each self-corresponding fusion amplitude range of described three fusion frequencies is normalized:

$A^{*}=\frac{A-\min A}{\max A-\min A}$

Wherein, A ^*represent the amplitude after normalization, A represents original amplitude, and minA represents three minimum amplitude merged in amplitude range, and maxA represents three peak swings merged in amplitude range.

The embodiment of the present invention additionally provides a kind of veneer microfacies inverting device, and to reach the object of Accurate Prediction sedimentary micro, this device comprises:

Reservoir thickness determination module, for selecting many mouthfuls of wells in work area, determines the reservoir thickness of the zone of interest of every mouthful of well in described many mouthfuls of wells;

Response frequency determination module, for boundary at the bottom of the reservoir of the zone of interest of every mouthful of well in described many mouthfuls of wells as assay surface, in seismic section, upwards first schedule time, downward second schedule time carry out tuning analysis as analysis window, to determine the response frequency of the zone of interest of every mouthful of well;

Response amplitude determination module, for extracting peak swing value along the zone of interest of every mouthful of well in described many mouthfuls of wells in single-frequency volume data, reads response amplitude according to described peak swing value at the correspondence position of every mouthful of well;

Sedimentary micro determination module, for determining the sedimentary micro type of every mouthful of well at well point place in described many mouthfuls of wells;

Microfacies thickness relationship determination module, for according to the sedimentary micro type determined and the described reservoir thickness determined, sets up the relation between sedimentary micro and reservoir thickness;

Thickness frequency relationship determination module, for according to the reservoir thickness determined and the response frequency determined, sets up the relation between reservoir thickness and response frequency;

Thickness amplitude relation determination module, for according to the reservoir thickness determined and the response amplitude determined, sets up the relation between reservoir thickness and response amplitude;

Microfacies frequency relation determination module, for according to the sedimentary micro type determined and the response frequency determined, sets up the relation between sedimentary micro and response frequency;

Microfacies amplitude relation determination module, for according to the sedimentary micro type determined and the response amplitude determined, sets up the relation between sedimentary micro and response amplitude;

Fusion frequency determination module, for selecting three fusion frequencies and each self-corresponding sedimentary micro according to the relation between described sedimentary micro and reservoir thickness, the relation between described sedimentary micro and response frequency, the relation between sedimentary micro and response amplitude and the relation between described reservoir thickness and response frequency;

Merge amplitude range determination module, for determining three each self-corresponding fusion amplitude ranges of fusion frequency according to the relation between described reservoir thickness and response frequency;

RGB Fusion Module, for carrying out RGB fusion according to each self-corresponding sedimentary micro of described three fusion frequencies and each self-corresponding fusion amplitude range to described three fusion frequencies, obtains veneer microfacies inversion result.

In one embodiment, described response frequency determination module comprises:

Frequency tuning range determining unit, for boundary at the bottom of the reservoir of the zone of interest of every mouthful of well in described many mouthfuls of wells as assay surface, upwards first schedule time, downward second schedule time in seismic section, Short Time Fourier Transform is carried out to geological data, obtains frequency tuning range;

Response frequency determining unit, for using described frequency tuning range as constraint, adopts maximum entropy method (MEM) to process described geological data, determines the response frequency of the zone of interest of every mouthful of well.

In one embodiment, described RGB Fusion Module comprises:

Normalization unit, for being normalized each self-corresponding fusion amplitude range of described three fusion frequencies;

Inverting unit, for by the fusion frequency after normalized and each self-corresponding sedimentary micro of described three fusion frequencies, carries out RGB fusion to described three fusion frequencies, obtains veneer microfacies inversion result.

In embodiments of the present invention, utilize the micro logging facies at well point place to demarcate RGB attribute fusion figure, to obtain predicting the outcome of sedimentary micro, particularly, by surveying well logging microfacies analysis, well logging interpretation, spectral factorization, X plot statistical study, the application of the technology such as RGB fusion, fully in conjunction with drilling well, geology and earthquake information, utilize the thought of inverting, propose the method for a kind of veneer microfacies inverting, by well logging, the constraint of well logging phase improves the rationality of RGB integration technology when predicting sedimentary micro, solve in prior art three frequencies cannot effectively determining to merge attribute in RGB integration technology, and cause predicting the inaccurate technical matters of the sedimentary micro obtained, reach the technique effect of Accurate Prediction sedimentary micro, further, decrease the multi-solution of the seismic properties forecasting techniques brought because geology is uncertain.

Accompanying drawing explanation

Accompanying drawing described herein is used to provide a further understanding of the present invention, forms a application's part, does not form limitation of the invention.In the accompanying drawings:

Fig. 1 is the method flow diagram of the veneer microfacies inversion method according to the embodiment of the present invention;

Fig. 2 connects well profile figure according to the tuned frequency based on Short Time Fourier Transform of the embodiment of the present invention;

Fig. 3 connects well profile figure according to the tuned frequency asked for through maximum entropy of the embodiment of the present invention;

Fig. 4 is electrofacies, response frequency, actual measurement thickness X plot according to the embodiment of the present invention;

Fig. 5 is the sedimentary micro prognostic chart without this method constraint;

The sedimentary micro prognostic chart that Fig. 6 obtains according to the method for the embodiment of the present invention;

Fig. 7 is the sedimentary micro prognostic chart giving prominence to point bar favorable facies belt after normalization according to the embodiment of the present invention;

Fig. 8 is the structured flowchart of the veneer microfacies inversion method device according to the embodiment of the present invention.

Embodiment

For making the object, technical solutions and advantages of the present invention clearly understand, below in conjunction with embodiment and accompanying drawing, the present invention is described in further details.At this, exemplary embodiment of the present invention and illustrating for explaining the present invention, but not as a limitation of the invention.

If using sedimentary micro (mf) as a model space, using log data (c) and geological data (s) as data space, so, for just drilling, just have:

sc＝Gmf

Wherein, G represents functional operator, and G can be an integral operator, differentiating operator, a matrix or a function, also can be a process.

For the situation that there is known log data (c) and geological data (s), the process asking for sedimentary micro (mf) is exactly inverting is topic, that is:

mf＝G ^-1(s,c)

Wherein, X plot can be G ^-1concrete manifestation form, fusion figure is the concrete methods of realizing of inverting.

Particularly, in this example, provide a kind of veneer microfacies inversion method, as shown in Figure 1, comprise the following steps:

Step 101: select many mouthfuls of wells in work area, determines the reservoir thickness of the zone of interest of every mouthful of well in described many mouthfuls of wells;

Particularly, select many mouthfuls of wells in work area after, by the well logging interpretation to every mouthful of well, the reservoir thickness of every mouthful of well can be determined;

Such as, from work area, have selected 19 mouthfuls of wells, according to the logging trace in this work area and mud logging technique, the reservoir thickness of the zone of interest of every mouthful of well is added up.Such as, if the objective interval in this district is based on sand shale, spontaneous potential (SP) curve then can be adopted to determine the reservoir thickness of the zone of interest of every mouthful of well, particularly, first the shale line of SP is determined, corresponding to large section shale layer part, the unusual part of now departing from shale line can think it is reservoir, and abnormal amplitudes larger explanation shale index is fewer.After identifying pervious course, can with at the bottom of the top of the method division of reservoir of " half range point ", thus determine the thickness of reservoir, finally can carry out contrast by mud logging technique to reservoir thickness and correct, thus finally determine the reservoir thickness of the zone of interest of every mouthful of well.

Step 102: in described many mouthfuls of wells the zone of interest of every mouthful of well reservoir at the bottom of boundary as assay surface, in seismic section, upwards first schedule time, downward second schedule time carry out tuning analysis as analysis window, to determine the response frequency of the zone of interest of every mouthful of well;

In the process that reality performs, first can carry out horizon calibration, at the tracing of horizons of the whole district (i.e. full work area) this interpretation horizon after demarcation, and using this interpretation horizon as assay surface to boundary at the bottom of the reservoir of the zone of interest of every mouthful of well in many mouthfuls of wells.

Particularly, can using the end circle of zone of interest as assay surface (namely using the lower boundary of the reservoir determined as assay surface), upwards 50ms, downward 10ms is as analysis window.It is so-called that what upwards refer to downwards is in seismic section, because being represent position of stratum with the time in seismic section, therefore after determining assay surface, certain time point in seismic section can be mapped to, then upwards get predetermined time downwards, just can obtain an analysis window.After determining analysis window, tuning analysis can be carried out with Short Time Fourier Transform method and maximum entropy method (MEM) respectively.

In this example, be why consider that Fourier's method of changing is relatively stable in short-term by Short Time Fourier Transform method and maximum entropy method (MEM), but be subject to the restriction of solid timing window, frequency resolution is low, and maximum entropy method when asking for tuned frequency frequency resolution high, but easily bring Algorithm Error into.Therefore, inventor expects first to use Short Time Fourier Transform method determination frequency tuning range, then applies maximum entropy method (MEM) and determines the response frequency of every mouthful of well at zone of interest.The tuned frequency be illustrated in figure 2 based on Short Time Fourier Transform connects well profile figure, is illustrated in figure 3 the tuned frequency asked for through maximum entropy and connects well profile figure.

Particularly, the operational formula of Short Time Fourier Transform method is:

$s(f,\mathrm{\&tau;})=\frac{1}{\sqrt{2\mathrm{\&pi;}}}\&Integral;s\left(t\right)w(t-\mathrm{\&tau;})e^{-j2\mathrm{\&pi;}ft}dt$

Wherein, s (t) represents geological data, and w (t-τ) is expressed as window letter, and f represents response frequency, and t represents the time.

Maximum entropy method (MEM) comprises:

First by following K rank autoregression difference equation simulated earthquake data:

$x\left(t\right)-\underset{k=1}{\overset{K}{\&Sigma;}}{\mathrm{\&alpha;}}_k{x}_{t-k}=e\left(t\right)$

Wherein, x (t) represents the seismic trace of geological data; α _krepresent autoregressive coefficient, and | α _k| <1, k=1,2 ..., e (t) represents predicated error, is a white noise sequence, and K=2N/ln (2N), wherein, N represents the length of seismologic record.

Then, autoregressive coefficient α is obtained according to described K rank auto-regressive equation _ppafter variance, by following formulae discovery power spectrum:

$P\left(f\right)=\frac{{{\mathrm{\&delta;}}_k}^2}{{\left|1-\underset{m=1}{\overset{K}{\&Sigma;}}{\mathrm{\&alpha;}}_{mm}{e}^{-j2\mathrm{\&pi;}fm\mathrm{\&Delta;}t}\right|}^2}$

Wherein, P (f) represents estimated power spectrum, represent the variance of e (t), α _mmrepresent autoregressive coefficient, f represents response frequency, and t represents the time.

Finally, from power spectrum, determine the response frequency of the zone of interest of every mouthful of well.

Because Short Time Fourier Transform, algorithmic stability but frequency resolution is low, frequency tuning range can be obtained by this, then maximum entropy method (MEM) is adopted to process geological data again, maximum entropy method (MEM), algorithm frequency resolution is high, but easily introduces Algorithm Error, and under the constraint of the scope obtained in Short Time Fourier Transform, two methods combine the response frequency accurately can determining the zone of interest of every mouthful of well.

Step 103: extract peak swing value along the zone of interest of every mouthful of well in described many mouthfuls of wells in single-frequency volume data, reads response amplitude according to described peak swing value at the correspondence position of every mouthful of well;

Different from response frequency, the determination of response amplitude needs to carry out at single-frequency body, can apply Wavelet Transform and ask for single-frequency body, for arbitrary function f (t) ∈ L ²(R), its continuous wavelet transform is:

$W_{\mathrm{\&psi;}}f(a,b)=\frac{1}{\sqrt{\left|a\right|}}{\&Integral;}_{-\mathrm{\&infin;}}^{+\mathrm{\&infin;}}f\left(t\right)\mathrm{\&psi;}*\left(\frac{t-b}{a}\right)dt$

Wherein, W _ψrepresent signal time-size distribution, a represents scale factor, and b represents shift factor, and ψ represents a morther wavelet, and f represents response frequency, and t represents the time, L ²(R) quadractically integrable function space is represented.

After obtaining single-frequency body, extract peak swing value along zone of interest in single-frequency body, then response amplitude value is read in the relevant position of corresponding every mouthful of well.

Step 104: determine the sedimentary micro type of every mouthful of well at well point place in described many mouthfuls of wells, the sedimentary micro type at well point place can be determined by microfacies sedimentation analysis method;

Still for above-mentioned 19 mouthfuls of wells, when the sedimentary micro determining well point place, generally need consideration two factors, one is micro logging facies, and two is seismic section phases.When the determination carrying out sedimentary micro, can first by the difference of deposition phase corresponding to the tracing patterns such as bell, box, sawtooth pattern, the linear pattern of logging trace, mark geological data with micro logging facies, and then determined the type of sedimentary micro at well point place by the identification of seismic section phase.

Step 105: according to the sedimentary micro type determined and the described reservoir thickness determined, set up the relation between sedimentary micro and reservoir thickness;

For the relation of sedimentary micro and reservoir thickness, can quote theory the most classical in sedimentology to prove, that is, for terrestrial lake basin deposition, distance thing source be nearer, and reservoir is educated all the more, and thickness is larger.From sedimentary facies, braided stream deposit environment facies are than meandering stream deposit environment, and pigtail river facies reservoir thickness is larger, this point sufficient proof, there is close relationship between reservoir thickness and sedimentary facies belt.In practical application, on the basis that geologic background is fully realized, the conclusion that utilization can utilize above-mentioned steps 101 and above-mentioned steps 104 to obtain, set up the relation between reservoir thickness and sedimentary micro, in this example, the pass obtained is: point bar microfacies reservoir thickness is the thickest, and raised bank is relatively thin, and valley flat is without reservoir.

Step 106: according to the reservoir thickness determined and the response frequency determined, set up the relation between reservoir thickness and response frequency;

Concrete, in this example, the pass in whole study area between reservoir thickness and response frequency is:

y＝-0.5606x+34.378

For point bar microfacies, the pass of reservoir thickness and response frequency is:

y＝-0.4043x+29.913

Wherein, x represents response frequency, and y represents reservoir thickness.

Particularly, as shown in Figure 4, be sedimentary micro and reservoir thickness, relation schematic diagram between reservoir thickness and response frequency.Raised bank and valley flat very thin due to reservoir deposit thickness, consider that seismic data is band-limited signal, the reservoir that very difficult resolution is very thin, therefore can be referred to as sailaba parfacies by unified for these two microfacies, research and analyse together.

Step 107: according to the reservoir thickness determined and the response amplitude determined, set up the relation between reservoir thickness and response amplitude;

Step 108: according to the sedimentary micro type determined and the response frequency determined, set up the relation between sedimentary micro and response frequency;

Particularly, can pass through step 101, step 102 and step 104 take reservoir thickness as bridge, by the relation between the method establishment sedimentary micro of three parameter X plot statistical study and response frequency.

Step 109: according to the sedimentary micro type determined and the response amplitude determined, set up the relation between sedimentary micro and response amplitude;

Particularly, can pass through step 101, step 103 and step 104 take reservoir thickness as bridge, by the relation between the method establishment sedimentary micro of three parameter X plot statistical study and response amplitude.

Step 110: select three fusion frequencies and each self-corresponding sedimentary micro according to the relation between described sedimentary micro and reservoir thickness, the relation between described sedimentary micro and response frequency, the relation between sedimentary micro and response amplitude and the relation between described reservoir thickness and response frequency;

In this example, corresponding thick layer deposition (exceeding tuning thickness) frequency range is f<20Hz, 15Hz can be selected to participate in merging, meandering river point bar microfacies response frequency scope is 20Hz<f<45Hz, 35Hz can be selected to participate in merging, and be f>45Hz for the response frequency scope of valley flat and raised bank, 60Hz can be selected to participate in merging.Be illustrated in figure 5 the sedimentary micro prognostic chart without this method constraint, be illustrated in figure 6 the sedimentary micro prognostic chart obtained by this method.

Step 111: determine three each self-corresponding fusion amplitude ranges of fusion frequency according to the relation between described reservoir thickness and response frequency;

In this example, the response amplitude scope of corresponding 15Hz single-frequency body (corresponding to thick layer deposition) is 2500<A<5700, the response amplitude scope of corresponding 35Hz single-frequency body (meandering river point bar microfacies) is 28000<A<50000, and the response amplitude scope of corresponding 60Hz single-frequency body (valley flat and raised bank) is 8100<A<12600.

After determining that three participate in the single-frequency body merged, standardization is carried out to it, particularly, standardization can be carried out according to following formula:

$A^{*}=\frac{A-\min A}{\max A-\min A}$

Wherein, A ^*represent the amplitude after normalization, A represents original amplitude, and minA represents three minimum amplitude merged in amplitude range, and maxA represents three peak swings merged in amplitude range.

Normalized object is the amplitude range participating in three the single-frequency bodies merged to be adjusted to (0-1) in unified scope, and then the single-frequency body of three after normalization is carried out RGB fusion, such 15Hz single-frequency body selects amplitude range to be 0-0.07,35Hz single-frequency body selects amplitude range to be 0.53-1,60Hz single-frequency body selects amplitude range to be 0.12-0.22, be conducive to outstanding favorable facies belt by normalized, be illustrated in figure 7 the sedimentary micro prognostic chart of outstanding point bar favorable facies belt after normalization.

Step 112: according to each self-corresponding sedimentary micro of described three fusion frequencies and each self-corresponding fusion amplitude range, RGB fusion is carried out to described three fusion frequencies, obtain veneer microfacies inversion result.

Particularly, on the basis of the fusion frequency of step 110 selection, the fusion amplitude range that integrating step 111 provides, 3 single-frequency bodies are selected to carry out RGB fusion, such as: 15Hz single-frequency body is red, 35Hz single-frequency body is green, and 60Hz single-frequency body is blue, then can extract horizon slice to fusion along zone of interest.

In the above-described embodiments, utilize the micro logging facies at well point place to demarcate RGB attribute fusion figure, to obtain predicting the outcome of sedimentary micro, particularly, by surveying well logging microfacies analysis, well logging interpretation, spectral factorization, X plot statistical study, the application of the technology such as RGB fusion, fully in conjunction with drilling well, geology and earthquake information, utilize the thought of inverting, propose the method for a kind of veneer microfacies inverting, by well logging, the constraint of well logging phase improves the rationality of RGB integration technology when predicting sedimentary micro, decrease the multi-solution of the seismic properties forecasting techniques brought because geology is uncertain.Further, the veneer microfacies inversion method proposed by this example also can to have the prediction of clear and rational to meandering river point bar, branch channel, sailaba equiphase zone, and sufficient proof the method has good effect.

Based on same inventive concept, additionally provide a kind of veneer microfacies inverting device in the embodiment of the present invention, as described in the following examples.The principle of dealing with problems due to veneer microfacies inverting device is similar to veneer microfacies inversion method, and therefore the enforcement of veneer microfacies inverting device see the enforcement of veneer microfacies inversion method, can repeat part and repeat no more.Following used, term " unit " or " module " can realize the software of predetermined function and/or the combination of hardware.Although the device described by following examples preferably realizes with software, hardware, or the realization of the combination of software and hardware also may and conceived.Fig. 8 is a kind of structured flowchart of the veneer microfacies inverting device of the embodiment of the present invention, as shown in Figure 8, comprise: reservoir thickness determination module 801, response frequency determination module 802, response amplitude determination module 803, sedimentary micro determination module 804, microfacies thickness relationship determination module 805, thickness frequency relationship determination module 806, thickness amplitude relation determination module 807, microfacies frequency relation determination module 808, microfacies amplitude relation determination module 809, fusion frequency determination module 810, merge amplitude range determination module 811 and RGB Fusion Module 812, below this structure is described.

Reservoir thickness determination module 801, for selecting many mouthfuls of wells in work area, determines the reservoir thickness of the zone of interest of every mouthful of well in described many mouthfuls of wells;

Response frequency determination module 802, for boundary at the bottom of the reservoir of the zone of interest of every mouthful of well in described many mouthfuls of wells as assay surface, in seismic section, upwards first schedule time, downward second schedule time carry out tuning analysis as analysis window, to determine the response frequency of the zone of interest of every mouthful of well;

Response amplitude determination module 803, for extracting peak swing value along the zone of interest of every mouthful of well in described many mouthfuls of wells in single-frequency volume data, reads response amplitude according to described peak swing value at the correspondence position of every mouthful of well;

Sedimentary micro determination module 804, for determining the sedimentary micro type of every mouthful of well at well point place in described many mouthfuls of wells;

Microfacies thickness relationship determination module 805, for according to the sedimentary micro type determined and the described reservoir thickness determined, sets up the relation between sedimentary micro and reservoir thickness;

Thickness frequency relationship determination module 806, for according to the reservoir thickness determined and the response frequency determined, sets up the relation between reservoir thickness and response frequency;

Thickness amplitude relation determination module 807, for according to the reservoir thickness determined and the response amplitude determined, sets up the relation between reservoir thickness and response amplitude;

Microfacies frequency relation determination module 808, for according to the sedimentary micro type determined and the response frequency determined, sets up the relation between sedimentary micro and response frequency;

Microfacies amplitude relation determination module 809, for according to the sedimentary micro type determined and the response amplitude determined, sets up the relation between sedimentary micro and response amplitude;

Fusion frequency determination module 810, for selecting three fusion frequencies and each self-corresponding sedimentary micro according to the relation between described sedimentary micro and reservoir thickness, the relation between described sedimentary micro and response frequency, the relation between sedimentary micro and response amplitude and the relation between described reservoir thickness and response frequency;

Merge amplitude range determination module 811, for determining three each self-corresponding fusion amplitude ranges of fusion frequency according to the relation between described reservoir thickness and response frequency;

RGB Fusion Module 812, for carrying out RGB fusion according to each self-corresponding sedimentary micro of described three fusion frequencies and each self-corresponding fusion amplitude range to described three fusion frequencies, obtains veneer microfacies inversion result.

In one embodiment, response frequency determination module 802 comprises: frequency tuning range determining unit, for boundary at the bottom of the reservoir of the zone of interest of every mouthful of well in described many mouthfuls of wells as assay surface, upwards first schedule time, downward second schedule time in seismic section, Short Time Fourier Transform is carried out to geological data, obtains frequency tuning range; Response frequency determining unit, for using described frequency tuning range as constraint, adopts maximum entropy method (MEM) to process described geological data, determines the response frequency of the zone of interest of every mouthful of well.

In one embodiment, RGB Fusion Module 812 comprises: normalization unit, for being normalized each self-corresponding fusion amplitude range of described three fusion frequencies; Inverting unit, for by the fusion frequency after normalized and each self-corresponding sedimentary micro of described three fusion frequencies, carries out RGB fusion to described three fusion frequencies, obtains veneer microfacies inversion result.

The formula used in the process of implementation for modules or unit is similar to above-mentioned veneer microfacies inversion method with concrete operations flow process, does not repeat them here.

In another embodiment, additionally provide a kind of software, this software is for performing the technical scheme described in above-described embodiment and preferred implementation.

In another embodiment, additionally provide a kind of storage medium, store above-mentioned software in this storage medium, this storage medium includes but not limited to: CD, floppy disk, hard disk, scratch pad memory etc.

From above description, can find out, the embodiment of the present invention achieves following technique effect: in the above-described embodiments, utilize the micro logging facies at well point place to demarcate RGB attribute fusion figure, to obtain predicting the outcome of sedimentary micro, particularly, by surveying well logging microfacies analysis, well logging interpretation, spectral factorization, X plot statistical study, the application of the technology such as RGB fusion, fully in conjunction with drilling well, geology and earthquake information, utilize the thought of inverting, propose the method for a kind of veneer microfacies inverting, by well logging, the constraint of well logging phase improves the rationality of RGB integration technology when predicting sedimentary micro, solve in prior art three frequencies cannot effectively determining to merge attribute in RGB integration technology, and cause predicting the inaccurate technical matters of the sedimentary micro obtained, reach the technique effect of Accurate Prediction sedimentary micro, further, decrease the multi-solution of the seismic properties forecasting techniques brought because geology is uncertain.

Obviously, those skilled in the art should be understood that, each module of the above-mentioned embodiment of the present invention or each step can realize with general calculation element, they can concentrate on single calculation element, or be distributed on network that multiple calculation element forms, alternatively, they can realize with the executable program code of calculation element, thus, they can be stored and be performed by calculation element in the storage device, and in some cases, step shown or described by can performing with the order be different from herein, or they are made into each integrated circuit modules respectively, or the multiple module in them or step are made into single integrated circuit module to realize.Like this, the embodiment of the present invention is not restricted to any specific hardware and software combination.

The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for a person skilled in the art, the embodiment of the present invention can have various modifications and variations.Within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.

Claims (10)

1. a veneer microfacies inversion method, is characterized in that, comprising:

In work area, select many mouthfuls of wells, determine the reservoir thickness of the zone of interest of every mouthful of well in described many mouthfuls of wells;

In described many mouthfuls of wells, the reservoir lower bound of the zone of interest of every mouthful of well is as assay surface, and in seismic section, upwards first schedule time, downward second schedule time carry out tuning analysis as analysis window, to determine the response frequency of the zone of interest of every mouthful of well;

In single-frequency volume data, extract peak swing value along the zone of interest of every mouthful of well in described many mouthfuls of wells, read response amplitude according to described peak swing value at the correspondence position of every mouthful of well;

Determine the sedimentary micro type of every mouthful of well at well point place in described many mouthfuls of wells;

According to the sedimentary micro type determined and the described reservoir thickness determined, set up the relation between sedimentary micro and reservoir thickness;

According to the reservoir thickness determined and the response frequency determined, set up the relation between reservoir thickness and response frequency;

According to the reservoir thickness determined and the response amplitude determined, set up the relation between reservoir thickness and response amplitude;

According to the sedimentary micro type determined and the response frequency determined, set up the relation between sedimentary micro and response frequency;

According to the sedimentary micro type determined and the response amplitude determined, set up the relation between sedimentary micro and response amplitude;

Three fusion frequencies and each self-corresponding sedimentary micro is selected according to the relation between described sedimentary micro and reservoir thickness, the relation between described sedimentary micro and response frequency, the relation between sedimentary micro and response amplitude and the relation between described reservoir thickness and response frequency;

Three each self-corresponding fusion amplitude ranges of fusion frequency are determined according to the relation between described reservoir thickness and response frequency;

According to each self-corresponding sedimentary micro of described three fusion frequencies and each self-corresponding fusion amplitude range, RGB fusion is carried out to described three fusion frequencies, obtain veneer microfacies inversion result.

2. the method for claim 1, it is characterized in that, in described many mouthfuls of wells the zone of interest of every mouthful of well reservoir at the bottom of boundary as assay surface, in seismic section, upwards first schedule time, downward second schedule time carry out tuning analysis as analysis window, to determine the response frequency of the zone of interest of every mouthful of well, comprising:

In described many mouthfuls of wells the zone of interest of every mouthful of well reservoir at the bottom of boundary as assay surface, upwards first schedule time, downward second schedule time in seismic section, Short Time Fourier Transform is carried out to geological data, obtains frequency tuning range;

Using described frequency tuning range as constraint, adopt maximum entropy method (MEM) to process described geological data, determine the response frequency of the zone of interest of every mouthful of well.

3. method as claimed in claim 2, is characterized in that, adopt following formula to carry out Short Time Fourier Transform:

$s(f,\mathrm{\&tau;})=\frac{1}{\sqrt{2\mathrm{\&pi;}}}\&Integral;s\left(t\right)w(t-\mathrm{\&tau;})e^{-j2\mathrm{\&pi;}ft}dt$

Wherein, s (t) represents geological data, and w (t-τ) is expressed as window function, and f represents response frequency, and t represents the time.

4. method as claimed in claim 2, is characterized in that, adopts maximum entropy method (MEM) to process described geological data, determines the response frequency of the zone of interest of every mouthful of well, comprising:

By following K rank autoregression difference equation simulated earthquake data, and obtain autoregressive coefficient and the variance of described K rank autoregression difference equation:

$x\left(t\right)-\underset{k=1}{\overset{K}{\&Sigma;}}{\mathrm{\&alpha;}}_k{x}_{t-k}=e\left(t\right)$

Wherein, x (t) represents the seismic trace of geological data; α _krepresent autoregressive coefficient, and | α _k| <1, k=1,2 ..., e (t) represents predicated error, is a white noise sequence, K=2N/ln (2N), and wherein, N represents the length of seismologic record;

According to described autoregressive coefficient and described variance, by following formulae discovery power spectrum:

$P\left(f\right)=\frac{{\mathrm{\&delta;}}_k^2}{|1-\underset{m=1}{\overset{K}{\&Sigma;}}{\mathrm{\&alpha;}}_{mm}{e}^{-j2\mathrm{\&pi;}fm\mathrm{\&Delta;}t}{|}^2}$

Wherein, P (f) represents estimated power spectrum, represent the variance of e (t), α _mmrepresent autoregressive coefficient, f represents response frequency, and t represents the time;

The response frequency of the zone of interest of every mouthful of well is determined from described power spectrum.

5. the method for claim 1, is characterized in that, described single-frequency volume data is asked for according to following formula:

For arbitrary function f (t) ∈ L ²(R), its continuous wavelet transform is:

$W_{\mathrm{\&psi;}}f(a,b)=\frac{1}{\sqrt{\left|a\right|}}{\&Integral;}_{-\mathrm{\&infin;}}^{+\mathrm{\&infin;}}f\left(t\right){\mathrm{\&psi;}}^{*}\left(\frac{t-b}{a}\right)dt$

Wherein, W _ψrepresent signal time-size distribution, a represents scale factor, and b represents shift factor, and ψ represents a morther wavelet, and f represents response frequency, and t represents the time, L ²(R) quadractically integrable function space is represented.

6. the method according to any one of claim 1 to 5, it is characterized in that, according to each self-corresponding sedimentary micro of described three fusion frequencies and each self-corresponding fusion amplitude range, RGB fusion is carried out to described three fusion frequencies, obtains veneer microfacies inversion result, comprising:

The each self-corresponding fusion amplitude range of described three fusion frequencies is normalized;

By the fusion frequency after normalized and each self-corresponding sedimentary micro of described three fusion frequencies, RGB fusion is carried out to described three fusion frequencies, obtains veneer microfacies inversion result.

7. method as claimed in claim 6, is characterized in that, be normalized according to following formula to each self-corresponding fusion amplitude range of described three fusion frequencies:

$A^{*}=\frac{A-\min A}{\max A-\min A}$

Wherein, A ^*represent the amplitude after normalization, A represents original amplitude, and minA represents three minimum amplitude merged in amplitude range, and maxA represents three peak swings merged in amplitude range.

8. a veneer microfacies inverting device, is characterized in that, comprising:

Reservoir thickness determination module, for selecting many mouthfuls of wells in work area, determines the reservoir thickness of the zone of interest of every mouthful of well in described many mouthfuls of wells;

Response frequency determination module, for boundary at the bottom of the reservoir of the zone of interest of every mouthful of well in described many mouthfuls of wells as assay surface, in seismic section, upwards first schedule time, downward second schedule time carry out tuning analysis as analysis window, to determine the response frequency of the zone of interest of every mouthful of well;

Response amplitude determination module, for extracting peak swing value along the zone of interest of every mouthful of well in described many mouthfuls of wells in single-frequency volume data, reads response amplitude according to described peak swing value at the correspondence position of every mouthful of well;

Sedimentary micro determination module, for determining the sedimentary micro type of every mouthful of well at well point place in described many mouthfuls of wells;

Microfacies thickness relationship determination module, for according to the sedimentary micro type determined and the described reservoir thickness determined, sets up the relation between sedimentary micro and reservoir thickness;

Thickness frequency relationship determination module, for according to the reservoir thickness determined and the response frequency determined, sets up the relation between reservoir thickness and response frequency;

Thickness amplitude relation determination module, for according to the reservoir thickness determined and the response amplitude determined, sets up the relation between reservoir thickness and response amplitude;

Microfacies frequency relation determination module, for according to the sedimentary micro type determined and the response frequency determined, sets up the relation between sedimentary micro and response frequency;

Microfacies amplitude relation determination module, for according to the sedimentary micro type determined and the response amplitude determined, sets up the relation between sedimentary micro and response amplitude;

Fusion frequency determination module, for selecting three fusion frequencies and each self-corresponding sedimentary micro according to the relation between described sedimentary micro and reservoir thickness, the relation between described sedimentary micro and response frequency, the relation between sedimentary micro and response amplitude and the relation between described reservoir thickness and response frequency;

Merge amplitude range determination module, for determining three each self-corresponding fusion amplitude ranges of fusion frequency according to the relation between described reservoir thickness and response frequency;

RGB Fusion Module, for carrying out RGB fusion according to each self-corresponding sedimentary micro of described three fusion frequencies and each self-corresponding fusion amplitude range to described three fusion frequencies, obtains veneer microfacies inversion result.

9. device as claimed in claim 8, it is characterized in that, described response frequency determination module comprises:

Frequency tuning range determining unit, for boundary at the bottom of the reservoir of the zone of interest of every mouthful of well in described many mouthfuls of wells as assay surface, upwards first schedule time, downward second schedule time in seismic section, Short Time Fourier Transform is carried out to geological data, obtains frequency tuning range;

Response frequency determining unit, for using described frequency tuning range as constraint, adopts maximum entropy method (MEM) to process described geological data, determines the response frequency of the zone of interest of every mouthful of well.

10. device as claimed in claim 8 or 9, it is characterized in that, described RGB Fusion Module comprises:

Normalization unit, for being normalized each self-corresponding fusion amplitude range of described three fusion frequencies;

Inverting unit, for by the fusion frequency after normalized and each self-corresponding sedimentary micro of described three fusion frequencies, carries out RGB fusion to described three fusion frequencies, obtains veneer microfacies inversion result.