Recognition and division method for shale deposition cycles of different scales

Abstract

The invention relates to the technical field of petroleum and natural gas exploration, in particular to an identification and division method for shale deposition cycles of different scales. Different-scale deposition cycles of shale may be controlled by different climate-driven mechanisms, and based on deposition rate evolution analysis, a depth domain is converted into a time domain by establishing a time scale; the method can compare the correspondence of dominant spectrum peaks in actual data with an eccentricity rate period, a slope period, an age difference period, a solar activity period and an El Nino-Southern oscillation period, breaks through the limitation that only single-scale shale deposition cycle analysis is focused in the prior art, and is based on multiple analysis and test means. The shale deposition cycle identification and division method from the ten-meter level to the meter level to the centimeter level to the millimeter level to the micron level is established, the precision of shale reservoir transverse comparison and small layer division is improved, and guidance can be provided for positioning of shale rich in organic matter.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas exploration, and in particular to a method for identifying and dividing shale sedimentary cycles of different scales, which can identify and divide shale sedimentary cycles of ten-meter level, meter level, centimeter level, millimeter level and micrometer level. Technical Background

[0002] my country's shale oil and gas reservoirs are mainly continental shales, which have strong heterogeneity and frequent phase changes. There are sedimentary cycles of different scales such as "ten-meter-meter-centimeter-millimeter-micrometer" in shales, which are the manifestations of climate driving mechanisms of different scales (Earth orbit changes, solar activity cycles, seasonal cycles, etc.) in sedimentary records. At present, relevant research and technical methods are focused on the identification of ten-meter-meter sedimentary cycles, that is, shale cycles driven by periodic changes in the eccentricity, slope, and precession of the Earth's orbital parameters (Milankovitch cycles), while for smaller centimeter-millimeter-micrometer sedimentary cycles, there is still a lack of stable and reliable identification and analysis technology. The driving mechanisms of centimeter-millimeter-micrometer sedimentary cycles may be solar activity (with a cycle of thousands of years, hundreds of years, and more than ten years), El Niño-Southern Oscillation (with a cycle of 2 to 7 years) and seasonal climate (with a cycle of 1 year), etc. The difficulty in identifying them lies in the recovery of the sedimentation rate. On the one hand, for most shale formations, radioactive dating data are relatively scarce and have large errors; on the other hand, using a uniform sedimentation rate to restore the entire core section or profile obviously ignores the fluctuations in the sedimentation rate and cannot meet the accuracy requirements for determining small-scale sedimentary cycles.

[0003] In summary, the existing technology has not yet formed a systematic, high-precision, low-cost, and high-efficiency method for identifying and dividing shale sedimentary cycles of different scales, such as ten meters, meters, centimeters, millimeters, and micrometers. Summary of the invention

[0004] In view of the problems existing in the prior art, the present invention provides a method for identifying and dividing shale sedimentary cycles of different scales, such as ten-meter level, meter level, centimeter level, millimeter level and micrometer level.

[0005] The specific technical solutions of the present invention are as follows: S1. Carry out decameter-level to meter-level sedimentary cycle analysis on the paleoclimate indicators of the whole core or the whole section. For drilling core, the paleoclimate indicators can be selected from sensitive logging curves; for field sections, the paleoclimate indicators can be selected from magnetic susceptibility, elements, carbon and oxygen isotope data collected through continuous and dense sampling.

[0006] S2. After linear interpolation and detrending of paleoclimate indicators, multi-window spectrum analysis was performed to identify dominant spectral peaks and compare them with theoretical periods of astronomical orbits (eccentricity, slope, precession), and Gaussian bandpass filtering was used to extract decameter-scale to meter-scale cycles recorded in the stratigraphic data.

[0007] S3. Restore the evolution of the entire sedimentation rate using the sliding window correlation coefficient method (eCOCO) or the eTimeOpt method, and compare it with the sedimentation rate estimated by dividing the cycle length by the cycle time in the multi-window spectrum analysis in step 2. If the two are consistent, it means that the sedimentation rate is reliable.

[0008] S4. Perform high-precision grayscale value extraction, magnetic susceptibility measurement, X-ray fluorescence scanning, etc. on the core section / profile section with stable sedimentation rate, perform multi-window spectrum analysis on the acquired data, and establish the time scale of this section based on the sedimentation rate of this section obtained in step 3 to identify the implied centimeter-level sedimentary cycles.

[0009] S5. Move to a smaller scale, grind rock sample thin sections, perform micro-area X-ray fluorescence scanning and electron probe line scanning on the thin sections, and establish a time scale for this section based on the sedimentation rate of this section obtained in step 3 to identify the implied millimeter-micrometer sedimentary cycles.

[0010] The present invention has the following beneficial effects: First, the present invention breaks through the limitation of previous focus on single-scale shale sedimentary cycle analysis. Based on a variety of analytical and testing methods, it establishes a method for identifying and dividing shale sedimentary cycles of different scales, from decameters to meters, centimeters to millimeters to micrometers, filling the gap in related technologies.

[0011] Second, the sedimentary cycles of shale at different scales may be controlled by different climate-driven mechanisms. Based on the analysis of sedimentation rate evolution, the present invention converts the depth domain into the time domain by establishing a time scale. The correspondence between the dominant spectral peaks in the actual data and the eccentricity cycle, slope cycle, precession cycle, solar activity cycle and El Niño-Southern Oscillation cycle can be compared to analyze the driving mechanisms of sedimentary cycles of shale at different scales.

[0012] Third, my country's shale oil and gas reservoirs are mainly continental shales, which have strong heterogeneity and frequent phase changes. The present invention improves the accuracy of lateral comparison and sub-layer division of shale reservoirs, and can provide guidance for the positioning of organic-rich shales. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A flow chart of a method provided by an embodiment of the present invention; Figure 2 This is the spectrum analysis diagram of Well N55X1; Figure 3Restore the sedimentary environment evolution map for Well N55X1 using the eTimeOpt method, and annotate the sedimentation rate estimated by the cycle length; Figure 4 The gray value, magnetic susceptibility, and XRF element scanning (Ca, Si, K, Fe, S, Ti) results of the core section 3551.3-3553.6 meters in Well N55X1 are shown, and a time scale is established based on the sedimentation rate of this section; Figure 5 This is the time domain spectrum analysis result of the core magnetic susceptibility, gray value, first principal component and second principal component of the N55X1 well 3551.3~3553.6 meters; Figure 6 This is the main component of the thin section element at 3552.1 meters in well N55X1 and the electron probe scanning result diagram; Figure 7 This is the result of time domain spectrum analysis of principal component elements in the 3552.1-meter thin section of well N55X1. DETAILED DESCRIPTION

[0014] The technical solution of the present invention will be described in detail below in conjunction with specific embodiments.

[0015] like Figure 1 As shown, the method for identifying the deep El Nino-Southern Oscillation cycle based on annual laminar layers of marine and lake sediments provided by the embodiment of the present invention comprises the following steps: S1. Carry out decameter-level to meter-level sedimentary cycle analysis on the paleoclimate indicators of the whole core or the whole section. For drilling core, the paleoclimate indicators can be selected from sensitive logging curves (such as natural gamma curves); for field sections, the paleoclimate indicators can be selected from magnetic susceptibility, elements, carbon and oxygen isotope data collected continuously and densely.

[0016] S2. After linear interpolation and detrending of paleoclimate indicators, multi-window spectrum analysis (MultitaperMethod) was performed to identify dominant spectral peaks and compare them with theoretical periods of astronomical orbits (eccentricity, slope, precession), and Gaussian bandpass filtering was used to extract decameter-scale to meter-scale cycles recorded in stratigraphic data.

[0017] S3. Restore the evolution of the entire sedimentation rate using the sliding window correlation coefficient method (eCOCO) or the eTimeOpt method, and compare it with the sedimentation rate estimated by dividing the cycle length by the cycle time in the multi-window spectrum analysis in step 2. If the two are consistent, it means that the sedimentation rate is reliable.

[0018] S4. Perform high-precision (1 cm spacing) grayscale value extraction, magnetic susceptibility measurement, X-ray fluorescence scanning, etc. on the core section / profile section with stable sedimentation rate, perform multi-window spectrum analysis on the acquired data, and establish the time scale of this section based on the sedimentation rate of this section obtained in step 3 to identify the implied centimeter-level sedimentary cycles.

[0019] S5. Move to a smaller scale and grind rock sample slices (3 cm long, 0.03 mm thick). Perform micro-area X-ray fluorescence scanning (10 micron spacing) and electron probe line scanning (5 micron spacing) on ​​the slices. Use the sedimentation rate of this section obtained in step S3 to establish the time scale for this section and identify the implied millimeter-micrometer sedimentation cycles.

[0020] Preferably, when a Gaussian bandpass filter is used in step S2, the selection of the width of the filter is very important. If the width is too large, it will cover the redundant noise peaks, and if the width is too small, the filter cannot contain the target spectrum peak. In step S3, caution should be exercised in selecting the sliding window size. If the window size is too large, many high-frequency signals will be missed, and if the window size is too small, the expression of low-frequency signals will be suppressed. The sliding window size is generally set to about 1.2 to 2 times the length of the maximum cycle (such as the long eccentricity cycle) to be identified.

[0021] Preferably, the results of step S2 and step S3 can be statistically verified by the TimeOpt method to exclude the null hypothesis test that there is no influence of astronomical cycles.

[0022] Preferably, in step S4, characteristic elements that are sensitive to climate change and sedimentary environment changes, such as silicon, calcium, iron, sulfur, titanium, etc., should be selected from a series of element results of XRF and micro-area XRF. Further preferably, the principal component analysis method can be used for the selected series of characteristic elements that can reflect ancient climate change to extract the principal components that can represent the volatility of the group of data.

[0023] Preferably, in step S5, if annual laminae are developed in the shale, that is, each annual laminae represents a deposition period of one year, an annual laminae time scale can be established by counting the number of annual laminae and measuring the thickness of the annual laminae layer by layer. The shale deposition rate limited by the annual laminae thickness is compared with the deposition rate of the section obtained in step S3. If the two are consistent, it means that the recovered deposition rate is reliable. On this basis, the carbon and oxygen isotopes of the annual laminae can be measured layer by layer by in-situ laser isotope technology, and the millimeter-micrometer deposition cycles contained therein can be analyzed. Example 1

[0024] (1) The GR (natural gamma) curve of the single well Niu 55 Slant 1 in the lower 3rd and upper 4th sub-members of the Shahejie Formation in the Dongying Sag in the Jiyang Depression was selected, with a depth range of 3334-3593 m.

[0025] (2) Linear interpolation and detrending (LOWESS method) of the GR curves were performed, and multi-window spectrum analysis and sliding window spectrum analysis were performed to identify the dominant spectral peaks, which corresponded to the decameter-level to meter-level eccentricity cycles, slope cycles, and precession cycles, such as Figure 2 shown.

[0026] (3) The eTimeOpt method was used to restore the evolution of the entire sedimentation rate and compare it with the sedimentation rate estimated by dividing the cycle length by the cycle time in the multi-window spectrum analysis in step S2. The two are relatively consistent, indicating that the sedimentation rate is reliable. Figure 3 shown.

[0027] (4) Grayscale scanning, magnetic susceptibility, and XRF element scanning (1 cm interval) were performed on the core section from 3551.3 to 3553.6 m in the Niu 55 Slant 1 well, and a time scale was established based on the sedimentation rate of this section, such as Figure 4 shown.

[0028] (5) Principal component analysis was performed on a series of XRF elements obtained in the previous step, and the representative first and second principal components were selected. Time domain spectrum analysis was performed on the magnetic susceptibility, grayscale value, and first and second principal components of the 3551.3-3553.6 m core section, and the semi-precession period of 11189-11489 years, and the 1161-1558 years (14 cm cycle), ~350 years (3 cm cycle), and 200-240 years (2 cm cycle) corresponding to the solar activity cycle were obtained, as shown in Figure 5. Figure 5 shown.

[0029] (6) Micro-area XRF element scanning and electron probe line scanning were performed on the 3552.1-meter thin section of Niu 55 Slant 1 Well, and principal component analysis was performed on a series of elements obtained from the micro-area XRF element scanning. The representative first principal component and second principal component were selected, such as Figure 6 shown.

[0030] (7) Performing time domain spectrum analysis on the first and second principal components of the elements obtained in the previous step, we obtain a 2.1-4.5 year period (221.6-474.8 μm cycle) corresponding to the El Niño-Southern Oscillation, as shown in Figure 7 shown.

[0031] The above contents are merely examples and explanations of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the invention or exceed the scope defined by the claims, they shall all fall within the protection scope of the present invention.

Claims

1. A method for identifying and dividing shale sedimentary cycles of different scales, characterized in that: The following steps are involved: S1. Conduct decameter- to meter-scale sedimentary cycle analysis on the entire core or entire profile. For drill cores, paleoclimate indicators are selected from sensitive well logs; for field profiles, paleoclimate indicators are selected from continuously and densely sampled magnetic susceptibility, element, and carbon and oxygen isotope data. S2. After linear interpolation and detrending of paleoclimate indicators, a multi-window spectrum analysis (MultitaperMethod) was performed to identify dominant spectral peaks and compare them with theoretical astronomical orbital periods. Gaussian bandpass filtering was used to extract decameter- to meter-scale sedimentary cycles recorded in the stratigraphic data. S3. Recover the full-segment sedimentation rate evolution using the sliding window correlation coefficient method (eCOCO) or the eTimeOpt method, and compare it with the sedimentation rate estimated by dividing the cycle length by the cycle time in the multi-window spectrum analysis in step S2. If the two are consistent, the sedimentation rate is reliable. S4: Perform 1-cm grayscale value extraction, magnetic susceptibility measurement, and X-ray fluorescence scanning on core sections and profile sections with stable sedimentation rates. Perform multi-window spectrum analysis on the acquired data and establish a time scale for that section based on the sedimentation rate obtained in S3 to identify the centimeter-scale sedimentation cycles. S5. Move to a smaller scale, grind thin sections of rock samples, perform micro-area X-ray fluorescence scanning and electron probe line scanning on the thin sections, and establish a time scale for this section based on the sedimentation rate of this section obtained in step S3 to identify the implied millimeter-micrometer sedimentation cycles.

2. The method for identifying and dividing shale sedimentary cycles of different scales according to claim 1, characterized in that: In step S1, the sensitive logging curve is a natural gamma ray curve.

3. The method for identifying and dividing shale sedimentary cycles of different scales according to claim 1, characterized in that: In step S2, the theoretical period of the astronomical orbit is eccentricity, slope, and precession.

4. The method for identifying and dividing shale sedimentary cycles of different scales according to claim 1, characterized in that: In step S3, the sliding window size is set to 1.2 to 2 times the maximum cycle length required to be identified.

5. The method for identifying and dividing shale sedimentary cycles of different scales according to claim 1, characterized in that: The results of step S2 and step S3 are statistically verified by the TimeOpt method to exclude the null hypothesis test that there is no astronomical cycle influence.

6. The method for identifying and dividing shale sedimentary cycles of different scales according to claim 1, characterized in that: In step S4, multi-window spectrum analysis selects characteristic elements silicon, calcium, iron, sulfur, and titanium that are sensitive to climate change and sedimentary environment changes, and uses the principal component analysis method for the selected characteristic elements to extract the principal components that can represent the volatility of the data set.

7. The method for identifying and dividing shale sedimentary cycles of different scales according to claim 1, characterized in that: In step S5, the rock sample slice has a specification of 3 cm in length and 0.03 mm in thickness, the micro-area X-ray fluorescence scanning pitch is 10 microns, and the electron probe line scanning pitch is 5 microns.

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