CN108919369B - A kind of method of quantitative judge Milankovitch Cycles - Google Patents
A kind of method of quantitative judge Milankovitch Cycles Download PDFInfo
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Abstract
The present invention relates to a kind of methods of quantitative judge Milankovitch Cycles, comprising the following steps: 1) proxy indicator for selecting gamma ray curve to identify as Milankovitch Cycles；2) natural gamma data are pre-processed；3) theoretical orbital period value is identified, obtains theoretical periodic set M；4) detailed process is as follows is identified to the Milankovitch Cycles in stratum: 1. the natural gamma data in formation at target locations is arranged；2. the natural gamma data to selected stratum carry out spectrum analysis；3. implementing matching, to obtain Milankovitch Cycles and the corresponding cycle thickness of Milankovitch Cycles.
Description
Technical field
The present invention relates to a kind of methods of quantitative judge Milankovitch Cycles, belong to geo-logical terrain technical field.
Background technique
The cyclically-varying of Earth's orbit geometric shape can also generate sediment filling while controlling climate change
Important influence, Milankovitch are to the quantitative description contacted between orbital elements (eccentricity, slope and the precession of the equinoxes) and weather
The important milestone of cyclical stratigraphy development, eccentricity, slope and the precession of the equinoxes corresponding period are collectively referred to as Milankovitch Cycles.
There are metastable proportionate relationships between Milankovitch Cycles at different levels, in the stratum of stably depositing environment relative incorporation, this
One ratio should be consistent with the ratio of stratigraphic cycles thickness at different levels.This is also the basis of Milankovitch Cycles research.Stably depositing
The rock core on stratum is appeared and proxy indicator associated with climate change is used equally for the research of Milankovitch Cycles.
Common Milankovitch Cycles recognition methods is, by carrying out spectrum analysis to Substitute Indexes data, by data
Frequency domain is converted to from Depth Domain, records the corresponding frequency of upward peak of confidence level on spectrogram, by will be between frequency
Proportionate relationship is compared with the proportionate relationship of theoretical orbital period, finds a set of frequencies group close with theoretical period proportional
It closes, the corresponding thickness of the combination of frequency is related with Milankovitch Cycles.Accordingly, it is determined that most being connect with theoretical orbital period ratio
Close combination of frequency is the committed step for identifying Milankovitch Cycles.At present to this crucial ring, mainly according to theoretical week
Phase ratio and frequency proportions approximation ratio pair, it is believed that the two is close, belongs to qualitative analysis judgement, does not quantitatively determine the two
Between degree of closeness, also can not just illustrate the ratio whether being also more nearly combine, will cause Milan section identified in this way
Tieing up odd cycle, there are deviations.When the formation at target locations thickness of analysis is larger, the crest frequency that spectrum analysis obtains is more, accordingly
Proportionate relationship combination between frequency is also more, and being found most by qualitative analysis has matching just to seem time-consuming and laborious, abnormal difficult.
Summary of the invention
In view of the above-mentioned problems, being utilized the object of the present invention is to provide a kind of method of quantitative judge Milankovitch Cycles
The Milankovitch Cycles that this method identifies are more accurate.
To achieve the above object, the invention adopts the following technical scheme: a kind of side of quantitative judge Milankovitch Cycles
Method, comprising the following steps:
1) proxy indicator for selecting gamma ray curve to identify as Milankovitch Cycles；
2) natural gamma data are pre-processed；
3) theoretical orbital period value is identified, the descending for obtaining the theoretical period arranges set M；
4) detailed process is as follows is identified to the Milankovitch Cycles in stratum:
1. being arranged to the natural gamma data in formation at target locations；
2. the natural gamma data to selected stratum carry out spectrum analysis, data are converted into frequency domain from Depth Domain, are obtained
After obtaining data frequency spectrum profile, the peak value corresponding frequency f, all frequency f for recording 90% confidence level or more respectively are denoted as ascending order
Set F={ x1,x2,...,xn}；Since period and frequency are in reciprocal relation, for the ease of comparing matching, then in set F
Frequency is inverted, obtains new frequency values inverse descending set T={ t1,t2,...,tn, while recording corresponding with the frequency
Spectral amplitude y, be denoted as descending set Y={ y1,y2,...,yn, to reflect the significance degree of frequency；
3. implementing matching: selecting N number of data at random from theoretical periodic set M, haveKind combination, is arranged in descending order
Column obtain line number and areColumns is the two-dimensional array K of N, makes the element under every kind of combination divided by least member in the combination,
New two-dimensional array L is obtained, the i-th row element list is Pi[N]={ pi(1),pi(2),...,pi(N) },
Two-dimensional array L is used to characterize the proportionate relationship in each theoretical cycle data combination between element, last column element value is 1；
N number of data are selected at random from frequency values inverse set T, are hadKind combination, arrangement obtains line number in descending order
ForColumns is the two-dimensional array R of N, makes the element under every kind of combination divided by least member in the combination, obtains new two
Dimension group S, jth row element list are Qj[N]={ qj(1),qj(2),...,qj(N) },Two-dimensional array S
For characterizing the proportionate relationship in each actual frequency data combination between element, last column element value is 1；
Introduce the difference that parameter σ carrys out two ratio data combination L and S of quantitatively characterizing, definition
σ (i, j)=[pi(1)-qj(1)]2+[pi(2)-qj(2)]2+...+[pi(N)-qj(N)]2
Wherein i is the rower of certain row data in theoretical period array,J is in actual frequency inverse array
The rower of certain row data,
Since Milankovitch Cycles are in the conspicuousness in earth history period, the significance degree of each frequency will also consider,
Therefore introducing another parameter lambda indicates the significance degree of frequency:
λ=z1+z2+...+zN, wherein z1, z2..., zNIt is the corresponding amplitude of jth row element in frequency inverse combination S respectively
Value；
It is arranged in descending order according to σ size, selects the smallest 5 kinds of combinations of σ, consider that each frequency is corresponding in every kind of combination of frequency
Amplitude is arranged by λ descending, finds the corresponding theoretical periodic ratio combination P of λ minimum valueiQ is combined with frequency reciprocal ratioj, and make λ
The smallest theory periodic ratio combines PiCorresponding theory period combination (the i-th row in array K) is to save in the stratum
Milankovitch Cycles make the smallest frequency reciprocal ratio combination Q of λjIt is each Milankovitch Cycles pair divided by the sampling interval
The cycle thickness answered.
It is as follows that preprocessing process is carried out to natural gamma data in the step 2): first using well curve as reference pair nature
Gamma data carries out environmental correction, then is standardized to it and makes to study the identical log scale having the same of each well in area
It is horizontal.
The step 4) 1. in, process that the natural gamma data in formation at target locations are arranged are as follows: follow-up well location
Individual-layer data determines analysis window, by natural gamma data preparation at it is respective when window single file, each file not two columns
According to first is classified as the depth data in equal sampling intervals, and secondary series is natural gamma data corresponding with depth data.
The invention adopts the above technical scheme, which has the following advantages: the present invention is determined theoretical by spectrum analysis
After peak frequency values in periodic quantity and actual formation, the difference size between both parameter σ characterizations ratio is introduced, according to σ value
It is preferred that going out the C close with theoretical period proportional (being generally less than equal to 5) a actual formation combination of frequency, further according to each combination of frequency
The sum of amplitude power sequence is dropped to it, therefrom select the maximum combination of amplitude as correspondingly with Milankovitch Cycles
Layer cycle, i.e. the cycle thickness are controlled by Milankovitch Cycles.The invention proposes a kind of quantitative identification Milankovitchs
The method in period, and the influence of amplitude is considered, therefore the result identified is more accurate.
Detailed description of the invention
Fig. 1 be in certain rift basin-after late Miocene series stratum calculates the theoretical value of eccentricity, slope and precession of the equinoxes variation,
Carry out the obtained result of spectrum analysis；Wherein, figure (a) is the eccentrically connecting that spectrum analysis identifies, figure (b) is frequency spectrum point
The slope period identified is analysed, figure (c) is the precessional cycle that spectrum analysis identifies；
Fig. 2 is-late Miocene series stratum GR result of spectrum analysis curve in certain rift basin.
Specific embodiment
The present invention is described in detail below with reference to the accompanying drawings and embodiments.
The invention proposes a kind of methods of quantitative judge Milankovitch Cycles, comprising the following steps:
1) proxy indicator for selecting gamma ray curve to identify as Milankovitch Cycles.
The rock core on stably depositing stratum, appear and proxy indicator associated with climate change be used equally for Milan section tie up
The research of odd cycle.Proxy indicator includes geochemical analysis data (such as δ for meeting sampling density requirement18O、δ13C、δ88Sr、CaCO3Content, phosphorus/titanium etc.) and can reflect geophysical parameters (such as magnetic susceptibility, gamma ray curve, the color of climate change
Rate etc.).Gamma ray log is the gamma radiated during measuring the radioactive element nuclear decay in rock stratum in well
The intensity of ray.Clay material and organic matter are stronger to the adsorption capacity of radioactive substance, and shale material grains are small, deposition
Slowly, so that radioactive element has time enough to separate from solution.Therefore, gamma ray curve is able to reflect deposition
Shale and content of organic matter variation in object, and then reflect palaeoenvironment and palaeoclimatic variation, it can be as Milankovitch week
The proxy indicator of phase research.In addition, due to including gamma ray curve in the logging program in nearly all oil field, so that should
Method also has generality easy to spread.
2) natural gamma data are pre-processed, specifically, first using well curve as reference pair natural gamma data into
Row environmental correction, then it is standardized makes to study the identical log marked level having the same of each well in area.
Before identifying to Milankovitch Cycles, in order to eliminate deviation caused by environmental factor, cycle is being carried out
Before stratigraphic analysis, environmental correction is carried out to GR data (natural gamma data) using well curve as reference curve.In addition, of the invention
Natural gamma absolute value is used, log data, can also be because of log-time other than being interfered by environmental factor and generating deviation
, logger type different with number and scale difference cause system deviation.In order to enhance comparing for log data between more wells
Property, guarantee the reliability of data used, after carrying out environmental correction to log, then it is standardized, makes to study area
The identical log marked level having the same of interior each well.Under normal circumstances, natural gamma data all equidistantly sample,
If there is non-equidistant data, resampling is carried out to it, it is ensured that data sampling interval is equal.Data prediction work is equal
It is completed by Forward log interpretation software.
3) theoretical orbital period value is identified, existing orbital elements calculation method can be used in specific recognition methods.
The variation of Earth orbital parameters is revolved around the sun while exerting one's influence to the earth due to being enclosed by earth-moon system
The influence of interaction is also changing with the ground moon.Earth's surface tidal friction power caused by ground moon gravitation and track gravity will affect
Earth rate and the figure of the earth keep the velocity of rotation of the earth slack-off, and the precession of the equinoxes and earth's axis slope period are elongated.Current track
In element factor calculation method, the representative are the schemes of the propositions such as Berger, Laskar, and wherein Laskar (2004) is proposed
Solution La (2004) has then comprehensively considered above-mentioned influence factor.By in certain rift basin-late Miocene series stratum for, use
La (2004) calculates the theory that this layer of position sedimentation time section 16Ma (1000000 years) changes to 5.3Ma eccentricity, slope and the precession of the equinoxes
Value, sampling interval are 1ka (thousand).It is above-mentioned spectrum analysis is carried out respectively to orbital period gross data after, identify 3 bias
Rate period 405ka, 125ka, 95ka, 2 slope periods 53ka, 40ka, 3 precessional cycles 24ka, 22ka, 19ka are managed for 8 totally
By the period, it is denoted as descending set M={ 405,125,95,53,40,24,22,19 }, as shown in Figure 1.These theoretical orbital periods
Between existing stable proportionate relationship, can be used as the benchmark of determining astrodisasters science.
4) detailed process is as follows is identified to the Milankovitch Cycles in stratum:
1. arranging to the natural gamma data in formation at target locations, follow-up well location individual-layer data determines analysis window, will
Natural gamma data preparation at it is respective when window single file, each file not two column data, first is classified as the equal sampling intervals
Depth data, secondary series are natural gamma data corresponding with depth data.
2. the natural gamma data to selected stratum carry out spectrum analysis, data are converted into frequency domain from Depth Domain, are obtained
After obtaining data frequency spectrum profile, the peak value corresponding frequency f, all frequency f for recording 90% confidence level or more respectively are denoted as ascending order
Set F={ x1,x2,...,xn}.Since period and frequency are in reciprocal relation, for the ease of comparing matching, then in set F
Frequency is inverted, obtains new frequency values inverse descending set T={ t1,t2,...,tn}.It records simultaneously corresponding with the frequency
Spectral amplitude y, be denoted as set Y={ y1,y2,...,yn, to reflect the significance degree of frequency.
Identification Milankovitch Cycles answer following several principles under a proportional relationship: 1. the ratio between spectral frequencies is closed
Being should be small as far as possible with the difference of theoretical period proportional, and general control is within 5%；2. the astronomy identified in one section of stratum
Number of cycles should be more as far as possible, and typically no less than 3；3. the deposition speed that the astrodisasters science identified is calculated with corresponding cycle thickness
Rate should meet research area's deposition rule.
3. implement matching, specifically:
N number of data are selected at random from theoretical periodic set M, are hadKind combination (general 3≤N≤8), in descending order
Arrangement obtains two-dimensional array K, which isColumns is N；Make the member under every kind of combination (certain a line in two-dimensional array)
Element is normalized divided by least member in the combination (i.e. the last one element), obtains new two-dimentional descending array L,
The array line number isColumns is N；Its i-th row element list is Pi[N]={ pi(1),pi(2),...,pi(N) },Two-dimensional array L can be used to characterize the proportionate relationship in each theoretical cycle data combination between element, last
One column element value is 1.
N number of data are selected at random from frequency values inverse set T, are hadKind combination, arrangement obtains two dimension in descending order
Array R, the array line number areColumns is N；Make the element under every kind of combination (certain a line in two-dimensional array) divided by the group
Least member (i.e. the last one element) is normalized in conjunction, obtains new two-dimensional array S, which is
Columns is N；Its jth row element list is Qj[N]={ qj(1),qj(2),...,qj(N) },Two-dimensional array S
The proportionate relationship in each actual frequency data combination between element can be used to characterize, last column element value is 1.
Introduce the difference that parameter σ carrys out two ratio data combination L and S of quantitatively characterizing, definition
σ (i, j)=[pi(1)-qj(1)]2+[pi(2)-qj(2)]2+...+[pi(N)-qj(N)]2
Wherein i is the rower of certain row data in theoretical period array,J is in actual frequency inverse array
The rower of certain row data,
Since Milankovitch Cycles are in the conspicuousness in earth history period, the significance degree of each frequency should also be examined
Consider, present invention introduces the significance degrees that parameter lambda indicates frequency:
λ=z1+z2+...+zN, wherein z1, z2..., zNIt is the corresponding amplitude of jth row element in frequency inverse combination S respectively
Value.
It is arranged in descending order according to σ size, selects the smallest 5 kinds of combinations of σ, consider that each frequency is corresponding in every kind of combination of frequency
Amplitude is arranged by λ descending, finds the corresponding theoretical periodic ratio combination P of λ minimum valueiQ is combined with frequency reciprocal ratioj.With make λ
The smallest theory periodic ratio combines PiCorresponding theory period combination (the i-th row in array K) is to save in the stratum
Milankovitch Cycles make the smallest frequency reciprocal ratio combination Q of λjIt is each Milankovitch Cycles pair divided by the sampling interval
The cycle thickness answered.
According to the Milankovitch Cycles and its corresponding cycle thickness identified, it is estimated that the deposition speed on the stratum
Rate, the result have to comply with area deposition changing rule, are unable to that deviation is excessive, and difference should be less than 10% under normal circumstances.Usually
Depth of stratum corresponding with gamma ray curve is to fathom, and when stratigraphic dip and larger hole angle, needs to measure ground
Thickness degree is corrected to TST (true strata thickness), to obtain more accurate deposition rate data.True deposition after only corrected
Rate is matched with area deposition rule, could finally think that the cycle identified is the stratum rotation controlled by Milankovitch Cycles
It returns.If differed greatly, in Ying Chongfu step 4) 3., the Milankovitch Cycles group of area deposition rule is met until finding
Conjunction and its corresponding cycle thickness.
Effect of the invention is illustrated with a specific embodiment below:
Using patent thinking of the invention and step, in certain rift basin-late Miocene series stratum carried out Milan section dimension
Odd cycle research, carries out application verification.Research area belongs to terrestrial facies fan delta front deposition, and stratum is mainly sand-mud interbed,
Climate factor influences significant.0.15 meter is divided between natural gamma data sampling, numeric distribution range 30-200API, stratum is inclined
7 degree of angle, 22 degree of hole angle.
To the laggard line frequency spectrum analysis of the GR data prediction on the stratum, the corresponding frequency of 17 peak values on spectrogram is recorded
Rate is denoted as ascending order set F, then inverted to the frequency in set F, obtains new frequency values inverse descending set T, and record
Under the corresponding amplitude of each frequency, be denoted as set Y.The inverse of frequency is corresponding cycle depth measurement thickness MD, true cycle thickness
TVT is equal to TST (true strata thickness), that is, Milankovitch Cycles of the MD multiplied by the cosine of the sum of stratigraphic dip and hole angle, after correction
Corresponding actual thickness can be evaluated whether more accurate deposition rate.
By taking N=5 as an example, i.e., selects 5 frequencies at random from set F and be normalized, select 5 at random from the theoretical period
A period and normalized carry out the matching analysis to the two using the automatch worked out based on Matlab.Difference σ
The smallest 5 kinds of combinations are shown in Table 1, and optimal selection when preferably obtain N=5 further according to amplitude Y is the combination 3 in table 1.
Therefore, 5 Milankovitch Cycles saved in the stratum are 125ka, 95ka, 53ka, 40ka and 24ka respectively, corresponding
Cycle thickness is 20.99m, 16.28m, 8.67m, 6.70m, 4.07m respectively, as shown in Figure 2.Same step can take it to N
His value is analyzed, and corresponding final combination, then the combination that N is not obtained simultaneously are sorted according to σ, with obtain it is final the most
Reliable Milankovitch Cycles and its corresponding cycle thickness data.This is the study found that the obtained period combination of when N=5
Be in the rift basin-late Miocene series stratum in the combination of optimal Michaelis period, illustrate to remain in the stratum 125ka, 95ka,
Five kinds of Milankovitch Cycles of 53ka, 40ka and 24ka.Deposition rate is calculated accordingly in 0.17m/ka or so, the result and investigation
Area deposition rule it is consistent, therefore, it is considered that this analysis result is reliable, accuracy is high.It can be seen that the present invention can be automatic
The Milankovitch Cycles retained in stratum are quickly recognized, and calculate corresponding deposition rate, for deepening Continental Facies Stratigraphy
Controlling Sedimentary Factors and Evolution are of great significance.This method is simple and efficient, has high application value.
Auto-matching result when table 1N=5
The various embodiments described above are merely to illustrate the present invention, and wherein the implementation steps etc. of method may be changed,
All equivalents and improvement carried out based on the technical solution of the present invention, should not exclude in protection scope of the present invention
Except.
Claims (3)
1. a kind of method of quantitative judge Milankovitch Cycles, comprising the following steps:
1) proxy indicator for selecting gamma ray curve to identify as Milankovitch Cycles；
2) natural gamma data are pre-processed；
3) theoretical orbital period value is identified, the descending for obtaining the theoretical period arranges set M；
4) detailed process is as follows is identified to the Milankovitch Cycles in stratum:
1. being arranged to the natural gamma data in formation at target locations；
2. the natural gamma data to selected stratum carry out spectrum analysis, data are converted into frequency domain from Depth Domain, obtain number
After frequency spectrum profile, the peak value corresponding frequency f, all frequency f for recording 90% confidence level or more respectively are denoted as ascending order set F
={ x1,x2,…,xn}；Since period and frequency are in reciprocal relation, for the ease of comparing matching, then the frequency in set F is taken
Inverse obtains new frequency values inverse descending set T={ t1,t2,…,tn, while recording frequency spectrum vibration corresponding with the frequency
Width y is denoted as descending set Y={ y1,y2,…,yn, to reflect the significance degree of frequency；
3. implementing matching: selecting N number of data at random from theoretical periodic set M, haveKind combination, arrangement obtains in descending order
Line number isColumns is the two-dimensional array K of N, makes the element under every kind of combination divided by least member in the combination, is obtained new
Two-dimensional array L, the i-th row element list be Pi[N]={ pi(1),pi(2),…,pi(N) },Two-dimemsional number
Group L is used to characterize the proportionate relationship in each theoretical cycle data combination between element, last column element value is 1；
N number of data are selected at random from frequency values inverse set T, are hadKind of combination, in descending order arrangement obtain line number and areColumns is the two-dimensional array R of N, makes the element under every kind of combination divided by least member in the combination, obtains new two dimension
Array S, jth row element list are Qj[N]={ qj(1),qj(2),…,qj(N) },Two-dimensional array S is used
Characterize the proportionate relationship in the combination of each actual frequency data between element, last column element value is 1；
Introduce the difference that parameter σ carrys out two ratio data combination L and S of quantitatively characterizing, definition
σ (i, j)=[pi(1)-qj(1)]2+[pi(2)-qj(2)]2+…+[pi(N)-qj(N)]2
Wherein i is the rower of certain row data in theoretical period array,J is certain row in actual frequency inverse array
The rower of data,
Since Milankovitch Cycles are in the conspicuousness in earth history period, the significance degree of each frequency will also consider, therefore
Introducing another parameter lambda indicates the significance degree of frequency:
λ=z1+z2+…+zN, wherein z1, z2..., zNIt is the corresponding amplitude of jth row element in frequency inverse combination S respectively；
It is arranged in descending order according to σ size, selects the smallest 5 kinds of combinations of σ, consider the corresponding vibration of each frequency in every kind of combination of frequency
Width is arranged by λ descending, finds the corresponding theoretical periodic ratio combination P of λ minimum valueiQ is combined with frequency reciprocal ratioj, and make λ most
Small theoretical periodic ratio combines PiCorresponding theory period combination is the Milankovitch Cycles saved in the stratum, makes λ
The smallest frequency reciprocal ratio combines QjIt is the corresponding cycle thickness of each Milankovitch Cycles divided by the sampling interval.
2. a kind of method of quantitative judge Milankovitch Cycles as described in claim 1, it is characterised in that: the step 2)
In to natural gamma data carry out preprocessing process it is as follows: first using well curve be reference pair natural gamma data progress environment school
Just, then to it being standardized makes to study the identical log marked level having the same of each well in area.
3. a kind of method of quantitative judge Milankovitch Cycles as described in claim 1, it is characterised in that: the step 4)
1. in, process that the natural gamma data in formation at target locations are arranged are as follows: when follow-up well location individual-layer data determines analysis
Window, by natural gamma data preparation at it is respective when window single file, each file not two column data, first is classified as etc. between sampling
Every depth data, secondary series is natural gamma data corresponding with depth data.
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| CN116859485A (en) * | 2023-06-27 | 2023-10-10 | 成都理工大学 | High-frequency sequence identification and comparison method, system, equipment and terminal |
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