Shale oil dessert guiding method based on all-component hydrocarbon correction and astronomical framework

Abstract

The invention belongs to the technical field of petroleum and natural gas geological exploration and development, and particularly relates to a shale oil dessert guiding method based on all-component hydrocarbon correction and an astronomical framework. The method comprises the following steps: 1, acquiring a shale full diameter or well wall coring sample of a target block and logging data; 2, performing controlled experiment treatment on the rock sample to obtain original pyrolysis parameters and light hydrocarbon loss; 3, constructing an all-component free hydrocarbon recovery model, and obtaining the corrected real free hydrocarbon content; 4, carrying out detrending and pre-whitening pretreatment on the natural gamma logging curve of the target well; 5, mapping the corrected total organic carbon and oil saturation index to the isochronous framework; 6, according to geochemical parameters, shale oil dessert grading evaluation standards are established, and dessert layers of a class I, a class II and a class III are divided; 7, based on stratigraphic framework and dessert layer phase distribution, horizontal well trajectory design and real-time geosteering are guided. And the longitudinal resolution and the transverse isochronism of sweet spot prediction are effectively improved.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas geological exploration and development technology, and specifically relates to an unconventional oil and gas resource evaluation technology, namely a shale oil sweet spot prediction and geological guidance method based on Milankovitch cycle theory and combined with high-precision geochemical correction. Background Technology

[0002] Shale oil exploration and development has become a key focus of the global petroleum industry. China is rich in continental shale oil resources, particularly in the Gulong Depression of the Songliao Basin, the Jimsar Depression of the Junggar Basin, and the Subei Basin, where massive shale oil resources have been discovered. However, compared with North American marine shale, Chinese continental shale oil is characterized by complex lithology, strong heterogeneity, a wide range of thermal evolution, and high content of heavy components, which poses a significant technical challenge to the accurate prediction of "sweet spots."

[0003] On the one hand, existing oil-bearing assessment techniques have shortcomings. Accurately evaluating the oil-bearing potential of shale is fundamental to finding "sweet spots." Currently, the industry widely uses the Rock-Eval rock pyrolysis technique to evaluate the oil-bearing potential of shale, with key parameters including free hydrocarbons (S1) and pyrolytic hydrocarbons (S2). However, for continental shale rich in heavy oil and bitumen, existing assessment methods suffer from two fatal systematic errors.

[0004] First, the loss of light hydrocarbons leads to an underestimation of S1. During the extraction of shale cores from thousands of meters underground to the surface, the release of temperature and pressure causes significant volatilization and loss of low-boiling-point light hydrocarbon components (C1-C14). Conventional rock-evalence analysis is typically performed at room temperature and cannot detect this lost light hydrocarbon. Studies have shown that in medium- to high-maturity shale, the loss of light hydrocarbons can account for 30% to 60% of the total in-situ oil content. Without compensation, the flowability of the shale will be severely underestimated.

[0005] Secondly, parameter distortion is caused by heavy hydrocarbon "crossing." Traditional Rock-Eval pyrolysis procedures typically use 300°C as the cut-off temperature. However, shale oil contains a large amount of high-molecular-weight heavy hydrocarbons (such as resins, asphaltenes, and high-carbon alkanes), whose boiling points are much higher than 300°C. Furthermore, the adsorption and swelling effects of kerogen cause some free oil to be bound within the kerogen network. During pyrolysis, this portion of heavy free oil cannot volatilize in the first stage (<300°C), but instead undergoes cracking or thermal desorption in the second stage (300°C-600°C). This phenomenon is called "heavy hydrocarbon crossing," and its direct consequences are: further underestimation (missing the detection of heavy components), while the potential for hydrocarbon generation is artificially overestimated (due to the inclusion of free oil). This leads to a severely underestimated calculated oil saturation index (OSI=S1 / TOC), even misleading the determination of sweet spot levels.

[0006] On the other hand, due to limitations in existing stratigraphic correlation and guidance techniques, although shale formations appear homogeneous on a macroscopic scale, their lithology, physical properties, and oil content exhibit strong heterogeneity at the microscopic scale, varying with the sedimentary environment. High-quality sweet spots are often thin (only a few meters) and vary rapidly laterally.

[0007] First, the accuracy of traditional stratigraphic correlation is insufficient. The accuracy of traditional biostratigraphy or lithostratigraphy correlation is usually on the order of millions of years or tens of meters, which cannot meet the needs of horizontal wells to travel through sweet spot boxes several meters thick.

[0008] Secondly, the lack of an isochronous framework makes it easy to penetrate sweet spots during long horizontal drilling operations due to microstructural undulations and fault influences. Conventional marker bed correlations often exhibit time-lapse phenomena. Milankovitch cycle theory posits that the periodic variations in Earth's orbital parameters (eccentricity, slope, precession) control the distribution of surface solar radiation, thereby driving the periodic evolution of paleoclimate and sedimentary environments. Among these, the short eccentricity period of 405 kyr is relatively stable throughout geological history and can be used as a "metronome" for geological dating. Astronomical time scales established using cyclic stratigraphy methods can achieve resolutions up to tens of thousands of years, capable of identifying sedimentary units at the meter or even sub-meter level. However, there are currently few reports of systematic methods that combine high-precision astrostratigraphic frameworks with rigorously calibrated geochemical sweet spot parameters. Therefore, there is an urgent need to develop a comprehensive prediction method that can simultaneously solve the geochemical correction problem of oil-bearing parameters and provide a high-resolution isochronous stratigraphic framework to guide efficient shale oil exploration. Summary of the Invention

[0009] To address the shortcomings of the aforementioned background technologies, this invention provides a shale oil sweet spot guidance method based on full-component hydrocarbon correction and astronomical framework. This method innovatively integrates precise quantitative correction from organic geochemistry with high-frequency isochronous correlation techniques from cyclic stratigraphy, aiming to achieve accurate characterization of shale oil sweet spots across multiple dimensions of "material-time-space".

[0010] This invention adopts the following technical solution: a shale oil sweet spot guidance method based on full-component hydrocarbon correction and astronomical framework, the shale oil sweet spot guidance method comprising the following steps: Step 1: Obtain full-diameter or wellbore core samples of the shale in the target block, as well as logging data of the same well section. The logging data should include at least the natural gamma ray GR curve, resistivity curve, and sonic transit time curve.

[0011] Multi-scale data acquisition was conducted using the systematic core well G3 in the Gulong Shale of the Songliao Basin, the target block, collecting full-diameter or sealed core samples. Some samples were immediately frozen in liquid nitrogen or sealed in containers for light hydrocarbon loss analysis; the remaining samples underwent routine processing. High-resolution logging data for the entire well section was also collected simultaneously (sampling interval 0.125m).

[0012] Step 2: Conduct controlled experiments on the core samples, including conventional pyrolysis analysis, cryogenic pyrolysis analysis with liquid nitrogen, and pyrolysis analysis of the residue after organic solvent extraction, to obtain the original pyrolysis parameters and the amount of light hydrocarbon loss.

[0013] Step 3: Construct a full-component free hydrocarbon recovery model, calculate the cross-layer heavy hydrocarbon amount ΔS2 and the light hydrocarbon recovery coefficient K, obtain the corrected full-component true free hydrocarbon content and the true pyrolysis hydrocarbon potential, and the calculation method is as follows: Step 1: Select representative shale samples, crush them to 80 - 100 mesh, and divide them into three groups: A, B, and C.

[0014] Step 2: Measure the light hydrocarbon retention and correction coefficient for the samples in Group A.

[0015] Step 3: Conduct conventional Rock-Eval pyrolysis (rock pyrolysis analysis) on the samples in Group B to measure the conventional free hydrocarbon S1 常 and the conventional pyrolysis hydrocarbon S2 常 .

[0016] Step 4: Conduct Soxhlet extraction of the samples in Group C with an organic solvent to remove the soluble organic matter until the solvent becomes colorless. After drying, conduct Rock-Eval pyrolysis to measure the residue pyrolysis hydrocarbon S2 残 ; The organic solvent is a mixed solution of dichloromethane (DCM) and methanol (MeOH), and the volume ratio is 93:7 to 2:1. The extraction temperature is set 5 - 10 °C higher than the boiling point of the solvent, and the extraction time is not less than 72 hours.

[0017] Step 5: Calculate the cross-layer heavy hydrocarbon amount ΔS2 by heavy hydrocarbon repositioning. ΔS2 = S2 常 - S2 残 , and calculate the repositioned heavy hydrocarbon content S1 according to the coking correction coefficient α. The value range of the coking correction coefficient α is 0.65 - 0.75. 重 = α × ΔS2.

[0018] Step 6: Determine the light hydrocarbon recovery coefficient K according to the shale vitrinite reflectance Ro. The value of the light hydrocarbon recovery coefficient K is as follows: When 0.5% < Ro < 0.7%, the value of K is 1.09 - 1.16; when 0.7% < Ro < 0.9%, the value of K is 1.16 - 1.30; when 0.9% < Ro < 1.1%, the value of K is 1.3 - 1.41; when Ro > 1.1%, the value of K is 1.41 - 1.52.

[0019] Step 7: Calculate the corrected full-component true free hydrocarbon, and calculate the corrected light hydrocarbon part S1 轻校正 , S1 轻校正 = S1 常 × k, and the final in-situ free hydrocarbon total amount S1校正 S1 is the sum of the correction amount for light hydrocarbons and the return amount for heavy hydrocarbons. 校正 =S1 轻校正 +S1 重 .

[0020] A geochemical correction model for all components of free hydrocarbons was established, addressing the characteristics of high heavy hydrocarbon content and easy loss of light hydrocarbons in continental shale. A dual correction model was developed, incorporating both "light hydrocarbon compensation" and "heavy hydrocarbon repositioning." Heavy hydrocarbon correction utilized a solvent extraction-dual pyrolysis method, comparing the Rock-Eval pyrolysis of the same sample before and after extraction. Through the synergistic effect of strongly polar and non-polar solvents, heavy oil adsorbed in pores and kerogen was thoroughly eluted, and the heavy oil components retained in the peak were quantified using the difference method. Light hydrocarbon correction was based on a comparison between frozen and conventional samples, establishing a light hydrocarbon loss compensation coefficient chart by combining the degree of thermal evolution (Ro). Full component recovery involved adding the corrected heavy hydrocarbons back to S1 and compensating for light hydrocarbons to obtain the true in-situ oil content.

[0021] Step 4: Perform detrending and pre-whitening preprocessing on the natural gamma logging curves of the entire well section of the target well, and use the multi-window spectral analysis (MTM) method to perform spectral scanning to identify the main cycle of the Milankovitch cycle.

[0022] The specific parameters for Multi-Window Spectral Analysis (MTM) are set as follows: Discrete spherical sequence (DPSS) is used as the time window function, the time-bandwidth product (NW) is set to 2 to 4, and the frequency resolution of the number of window functions (K) is not less than 0.001 cycles / m. The spectrum results are subjected to a harmonic F-test based on multi-window spectrum theory. This test is used to determine whether the peak value at each frequency point in the spectrum is significantly different from the preset background noise continuous spectrum. Only frequency peak values ​​with a confidence level higher than 95% are retained as valid Milankovitch signals.

[0023] Milankovitch Cycle Identification Based on MTM Spectral Analysis utilizes the natural gamma (GR) curve as a paleoclimate proxy. Preprocessing involves detrending the GR curve to eliminate tectonic subsidence background and pre-whitening to suppress red noise. Spectral analysis employs Multi-Window Spectral Analysis (MTM), setting specific time-bandwidth product (NW) and window function counts (K) to minimize spectral leakage and improve the signal-to-noise ratio. Period extraction uses the F-test to determine frequency peaks with significant confidence (>95%), focusing on long eccentricity periods around 405 kyr.

[0024] Step 5: Use a Gaussian bandpass filter to extract the 405 kyr long eccentricity periodic signal, establish an astronomical stratigraphic framework, and map the corrected total organic carbon (TOC) and oil saturation index (OSI) into the astronomical stratigraphic framework.

[0025] The construction of a high-resolution astronomical chronostratigraphic framework uses a Gaussian band-pass filter to extract the 405 kyr main periodic signal, converts the well logging curve in the depth domain into a time-domain sequence through tuning technology, and establishes a floating astronomical time scale (ATS). This framework can identify the isochronous maximum flooding surface (MFS) and sequence boundaries in the strata.

[0026] Step 6: Based on the corrected geochemical parameters, establish a classification and evaluation standard for shale oil sweet spots, and divide them into Class I, Class II, and Class III sweet layers.

[0027] The classification and evaluation standard for sweet spots is as follows: Class I sweet spots (enriched layers): TOC > 2.0% and the total-component free hydrocarbon content S1 > 6.0 mg / g; Class II sweet spots (potential layers): 1.0% < TOC < 2.0% and 4.0 < S1 < 6.0 mg / g; Class III sweet spots (non-sweet spots): TOC < 1.0% or S1 < 4.0 mg / g - 87.

[0028] Step 7: Based on the astronomical chronostratigraphic framework and the phase distribution of sweet layers, guide the horizontal well trajectory design and real-time geological steering.

[0029] Real-time geological steering is as follows: Before drilling, use the data of the pilot hole to establish a standard astronomical stratigraphic framework curve based on the 405 kyr cycle. During the drilling process, obtain the real-time LWD-GR data of natural gamma ray while drilling. Use the sliding window correlation comparison method to map the data while drilling to the standard astronomical stratigraphic framework in real time, calculate the current phase angle of the bit. When it is monitored that the bit phase deviates from the semi-cyclical phase interval corresponding to Class I sweet spots, adjust the well inclination angle to control the wellbore trajectory to remain within the sedimentary section of the maximum flooding surface of the short eccentricity cycle.

[0030] Furthermore, in the application of sweet spot classification and geological steering, project the corrected parameters obtained in Step 3 into the astronomical framework established in Step 5. It is found that high-quality sweet layers often correspond to the deep lake facies sedimentary period of the long eccentricity cycle (405 kyr).

[0031] Furthermore, the classification and evaluation establish quantitative standards for Class I, II, and III sweet spots based on the corrected parameters.

[0032] Furthermore, the steering strategy is to match the GR data while drilling to the astronomical framework phase in real time during horizontal well drilling, ensuring that the bit always travels within the specific phase corresponding to Class I sweet spots (such as the maximum value section of the long eccentricity).

[0033] The beneficial effects of the present invention: The present invention provides a shale oil sweet spot steering method based on total-component hydrocarbon correction and astronomical framework. It realizes the accurate characterization of shale oil sweet spots in multiple dimensions of "substance-time-space". Its main advantages are as follows: (1) It greatly improves the accuracy of resource evaluation. Through the heavy hydrocarbon correction formula, the corrected value is usually 2-4 times the conventional measurement value, and the index is significantly improved, so that the strata that were originally misjudged as "oil-poor" are re-recognized as high-yield sweet spots.

[0034] (2) True isochronous stratigraphic correlation was achieved, with the 405 kyr long eccentricity period exhibiting global isochronism. Based on this, the framework established eliminated correlation traps caused by lithofacies changes, making the Class I sweet spot layer, which is only a few meters thick, traceable and predictable over a horizontal distance of several kilometers.

[0035] (3) The geological guidance “target window” was quantified, and the vague lithological target window was transformed into a precise “phase target window” to guide the drill bit to drill at the optimal sequence position, which significantly improved the sweet spot drilling rate of horizontal wells. Attached Figure Description

[0036] Figure 1 Figure 1 This is a flowchart of a method for predicting sweet spots in shale oil.

[0037] Figure 2 A chart showing the relationship between the light hydrocarbon recovery coefficient (K) and the degree of thermal evolution (Ro) of the Gulong Shale.

[0038] Figure 3 This is the MTM power spectrum analysis diagram of the natural gamma logging curve.

[0039] Figure 4 This is a cross-sectional view comparing the dessert layering based on astronomical cycles and isochronous comparison.

[0040] Figure 5 This is a schematic diagram of geological guidance phase navigation for horizontal wells. Detailed Implementation

[0041] The following is combined with Figures 1-5 The specific implementation details, experimental data, and processing procedures of this invention will be further described in detail. This embodiment takes the exploration and development of pure shale oil in the Cretaceous Qingshankou Formation of the Songliao Basin in China as an example, but the method of this invention is also applicable to other terrestrial or marine organic-rich shale formations. Example

[0042] Reference Figure 1 and Figure 2 Heavy hydrocarbon correction experiments, targeting the high concentration and boiling point of heavy components in continental shale, quantitatively characterize the amount of "heavy hydrocarbon migration" by comparing pyrolysis parameters before and after extraction. The steps of the geological steering method for continental shale oil sweet spots, integrating full-component hydrocarbon correction with the astronomical cyclic stratigraphic framework, are as follows: Step 1: Obtain full-diameter or closed-circuit cored samples from the shale in the target block. Select the systematic coring well G3 in the Gulong Shale of the Songliao Basin in the target block and collect full-diameter or closed-circuit cored samples. Also collect logging data from the same well section, including at least the natural gamma ray (GR) curve, resistivity curve, and sonic transit time curve.

[0043] Step 2: Conduct controlled experimental processing on the core samples, including conventional pyrolysis analysis, liquid nitrogen cryogenic pyrolysis analysis, and residue pyrolysis analysis after organic solvent extraction, to obtain the original pyrolysis parameters and the amount of light hydrocarbon loss.

[0044] Step 3: Construct a full-component free hydrocarbon recovery model, calculate the amount of heavy hydrocarbons ΔS2 and the light hydrocarbon recovery coefficient K, and obtain the corrected true free hydrocarbon content and true pyrolysis hydrocarbon potential of the full components. The calculation method is as follows: Step 1: Select a core sample from the target section of the Qingshankou Formation, at a depth ranging from 2100.0m to 2200.5m. Immediately after extraction, clean the core sample to remove surface drilling fluid contamination, and rapidly pulverize it to 80-100 mesh (approximately 0.15mm-0.18mm particle size) at low temperature. Divide the uniformly mixed powder sample into three portions, A, B, and C, for different testing purposes.

[0045] Sample A (in-situ sample): approximately 50g, immediately placed in a nitrogen-filled sealed container or frozen in liquid nitrogen on-site to minimize the volatilization of light hydrocarbons, used to determine the amount of light hydrocarbons retained and the correction factor.

[0046] Sample B (routine sample): approximately 50g, dried and stored at room temperature (>48 hours) to simulate the conditions of routine rock physical analysis and for routine Rock-Eval pyrolysis analysis.

[0047] Sample C (extraction sample): approximately 100g, used for organic solvent extraction experiments to completely remove free hydrocarbons.

[0048] Step 2: Determine the light hydrocarbon retention and correction coefficient for the samples in group A.

[0049] Step 3: Perform routine Rock-Eval pyrolysis on group B samples. Take 50-70 mg of sample B and place it in a Rock-Eval 6 pyrolysis instrument for standard analysis. The temperature program is set as follows: hold at 300°C for 3 minutes to detect volatile free hydrocarbons (S1), then increase the temperature to 650°C at a rate of 25°C / min to detect cracked hydrocarbons (S2). The measured free hydrocarbon S1... 常 =2.1 mg / g, conventional pyrolysis hydrocarbon S2 常 =18.5 mg / g. At this point, the OSI of the sample was only 100 × 2.1 / TOC, indicating poor oil content.

[0050] Step 4: Perform Soxhlet extraction with organic solvent and pyrolysis of the residue on sample C. Take approximately 30g of sample C and place it in the filter paper tube of the Soxhlet extractor. Use a binary mixed solvent of dichloromethane (DCM) and methanol (MeOH) with a volume ratio of 93:7 to remove soluble organic matter until the solvent is colorless. This ratio utilizes the strong solubility of DCM for asphaltenes and saturated hydrocarbons, and the polarity of MeOH for gums and organic matter adsorbed on the clay surface, without damaging the main structure of kerogen. Set the water bath heating temperature of the solution to 85°C, ensuring the solvent is in a state of gentle reflux. Continuous extraction time should not be less than 72 hours, until the solvent in the reflux tube becomes completely colorless. A fluorescence irradiation experiment on the last drop of solvent shows no fluorescence reaction, proving that the free hydrocarbons have been completely extracted. Place the extracted residue in a vacuum drying oven and dry at 60°C for 24 hours to completely remove residual solvent and moisture. The dried C residue sample was subjected to Rock-Eval pyrolysis analysis, which was exactly the same as in step 3, and the free hydrocarbon S1 in the residue was measured. 残 ≈0 mg / g (verification of thorough extraction), residual pyrolysis hydrocarbon S2 残 =12.8mg / g.

[0051] Step 5: Calculate the relocation of heavy hydrocarbons, and calculate the amount of heavy hydrocarbons that have migrated through the intercalation, ΔS2, where ΔS2 = S2. 常 -S2 残 =18.5-12.8=5.7mg / g. This 5.7mg / g represents the heavy free oil with a boiling point above 300°C that can be eluted by the solvent during extraction. A coking correction factor α is introduced, considering that during the high-temperature (>300°C) pyrolysis of heavy oil in the pyrolyzer, some components undergo condensation reactions to form dead carbon, causing the FID detector to fail to detect this signal. Based on the simulation results of crude oil in this region, the coefficient α is set to 0.69. The heavy hydrocarbon content S1 after repositioning is calculated. 重 =α×△S2≈5.7×0.69=3.93mg / g.

[0052] Step 6: Determine the light hydrocarbon recovery coefficient K based on the vitrinite reflectance Ro of the shale. Light hydrocarbon compensation calculations compensate for the loss of light hydrocarbons (C6-C14) during core taking and preparation. The measured vitrinite reflectance Ro of the sample is 1.25%, indicating a mature to highly mature evolutionary stage. Figure 2 The light hydrocarbon recovery coefficient chart of the Gulong Shale (this chart was established based on the chromatographic comparison of liquid nitrogen frozen samples and conventional samples) shows that the light hydrocarbon recovery coefficient k is 1.45 when Ro=1.25%.

[0053] Step 7: Calculate the corrected true free hydrocarbons of the whole component, and calculate the corrected light hydrocarbon fraction S1. 轻校正 S1 轻校正 =S1 常×k=2.1×1.45≈3.05mg / g, the final total in-situ free hydrocarbons S1 校正 S1 is the sum of the correction amount for light hydrocarbons and the return amount for heavy hydrocarbons. 校正 =S1 轻校正 +S1 重 =3.05+3.93=6.98mg / g.

[0054] After the above corrections, the oil content of the shale sample increased from the original measurement of 2.1 mg / g to 6.98 mg / g, an increase of 2.3 times. If the TOC of the sample is 2.5%, the oil saturation index (OSI) jumps from 84 mg / g (non-sweet spot) to 279 mg / g (high-quality sweet spot), significantly altering the assessment of the resource potential of this stratigraphic unit.

[0055] Step 4: Perform detrending and pre-whitening preprocessing on the natural gamma logging curves of the entire well section of the target well, and use the multi-window spectral analysis (MTM) method to perform spectral scanning to identify the main cycle of the Milankovitch cycle.

[0056] Data preprocessing: Select the natural gamma (GR) logging curves of the entire section of the first section (Q1) of the Qingshankou Formation in the target well, with a section length of 100.5 meters.

[0057] Resampling: To meet the requirements of digital signal processing, the GR curve is linearly interpolated at fixed intervals of 0.125 meters to obtain time series data with equal intervals.

[0058] Detrending: To eliminate the long-wavelength trend background caused by basin tectonic subsidence and compaction, the LOWESS (Locally Weighted Regression Scatter Smoothing) method was used, with the window length set to 35% of the total data length. The fitted trend line was subtracted from the original curve, and the residual sequence reflecting the periodic changes in paleoclimate was retained.

[0059] Pre-whitening: To suppress red noise interference commonly found in geological data and balance spectral energy, the detrended data undergoes first-order differencing, as shown in the formula: In the formula, x ' t x represents the pre-whitened data value. t-1 x is the data value of the previous sampling point. t This represents the data value of the current sampling point.

[0060] Multi-window spectral analysis (MTM) parameters were set using the MTM algorithm in Acycle software for spectral scanning. This method effectively reduces spectral leakage and improves the signal-to-noise ratio. The time-bandwidth product (NW) was set to 2, which controls the balance between spectral resolution and variance. NW=2 is suitable for processing shorter sedimentary sequences. The number of push-pull windows was set to 3 (i.e., 2×NW-1), using a discrete oblate spheroid sequence as the orthogonal window function. The frequency scan range was 0 - 0.1 cycles / meter. The significance test was performed using the F-test, with a confidence level of 95%, retaining only spectral peaks exceeding this confidence threshold. In the results interpretation and tuning, the spectral characteristics showed several significant energy peaks in the MTM power spectrum, corresponding to formation wavelengths of approximately 25m and 6.25m, respectively. Period identification was performed based on the theoretical astronomical period ratio and regional sedimentary background of this geological period (Cretaceous). A 25m wavelength corresponds to a long eccentricity period of 405 kyr, and a 6.25m wavelength corresponds to a short eccentricity period of 100 kyr. Stability verification showed that the 25m periodic signal had the strongest energy and best continuity throughout the entire well section, meeting the characteristics of a "geological metronome," and was therefore selected as the target tuning curve. In the filter design and framework, the center frequency of the Gaussian filter was f = 1 / 40.5 ≈ 0.0247 cycles / m. c The passband range is set to 0.020-0.030 cycles / m.

[0061] Step 5: Extract the 405 kyr long eccentricity periodic signal using a Gaussian bandpass filter, establish an astronomical stratigraphic framework, and map the corrected total organic carbon (TOC) and oil saturation index (OSI) into the astronomical stratigraphic framework. Spectral analysis and astronomical stratigraphic framework construction are as follows: Figure 3 As shown.

[0062] The GR curve is passed through this filter to extract the cyclic wave curve at 405 kyr. Each peak of the filtered curve (representing the short eccentricity maxima, i.e., the maximum flooding surface) is anchored to the time axis of the standard astronomical solution (La2010), thereby establishing a high-precision "depth-time" conversion scale and realizing the isochronous division of the stratigraphic framework.

[0063] Step Six: Based on the corrected geochemical parameters, establish a shale oil sweet spot grading and evaluation standard, classifying sweet spots into Class I, Class II, and Class III. The sweet spot grading and evaluation standard and its application are as follows: Figure 4 As shown. The corrected geochemical parameters (S1) 校正 The data is projected onto the established astronomical grid and combined with the oil production data from the test, to formulate a quantitative evaluation standard for shale oil sweet spots.

[0064] Category I (Core Dessert): 405kyr maximum period, deep lacustrine facies, well-developed bedding fractures; TOC ≥ 2.0%. After correction, the true free hydrocarbon content of the entire component is S1≥6.0mg / g, OSI≥300, and the cyclic phase characteristic is peak and vicinity (±π / 4 phase). The corresponding development strategy is horizontal well box core, close-cut fracturing. Category II sweet spot (potential sweet spot): Eccentricity transition period, semi-deep lacustrine facies, TOC 1.0%-2.0%, corrected S1 4.0-6.0mg / g, OSI 200−300, cyclic phase characteristic is rising or falling edge. The corresponding development strategy is replacement layer, requiring increased stimulation scale. Category III sweet spot (non-sweet spot): Eccentricity minimum period, shallow lacustrine facies, TOC<1.0%, S1<4.0, OSI<200, cyclic phase characteristic is trough. The corresponding development strategy is no development for now.

[0065] Step 7: Based on the astronomical age stratigraphic framework and sweet spot phase distribution, guide the horizontal well trajectory design and real-time geological steering, such as... Figure 5 As shown, it has been applied in the field for geological steering of horizontal wells on the H platform of shale oil.

[0066] Pre-drilling prediction: Based on the pilot well analysis, the target body (Type I sweet spot) is predicted to be located at the bottom of the Q1 section of the Qingshankou Formation, corresponding to the third peak of the 405 kyr cycle, with a thickness of about 4-5 meters.

[0067] Monitoring while drilling: During horizontal well drilling, real-time transmission of LWD-GR data is performed. When the drill bit is at the center of the target, the GR value is maintained at 135-150 API.

[0068] Phase navigation: Using real-time sliding window MTM analysis, the phase angle of the drill bit trajectory in a 405 kyr cycle is calculated. When the phase angle is close to the center of the peak, the well inclination is maintained, and drilling is carried out with a stable inclination. When the GR value is monitored to drop below 120 API and the phase angle deviates beyond (entering the trough / shallowing trend), it indicates that the drill bit is at risk of drilling out of the top or bottom boundary.

[0069] Track adjustment: Based on the phase shift direction (upward or downward drift), the geological guide immediately issues adjustment instructions (such as a 0.5° reduction in inclination) to guide the drill bit back to the phase range with the maximum eccentricity of high GR and high oil content.

[0070] Application Results: The horizontal section of this well is 2200 meters long. After applying this method, the encounter rate of Class I sweet spots reached 94.5%, significantly higher than the 78% of the adjacent well. The cumulative oil production in the first year after fracturing was 45% higher than that of the adjacent well, fully verifying the effectiveness and economic value of this method.

[0071] The shale oil sweet spot guidance method based on full-component hydrocarbon correction and astronomical framework accurately restores the in-situ free hydrocarbon content by establishing a heavy hydrocarbon correction model and a light hydrocarbon loss compensation algorithm, thus solving the problem of distortion in traditional pyrolysis parameters. Natural gamma logging is used to identify 405kyr long eccentricity cycles, establishing a high-resolution astronomical stratigraphic framework. An integrated "TOC-oil-time" ternary coupled sweet spot evaluation system is constructed to guide real-time geological steering of horizontal wells. This method effectively improves the vertical resolution and horizontal isochronism of sweet spot prediction, providing support for efficient shale oil exploration.

Claims

1. A shale oil sweet spot guidance method based on full-component hydrocarbon correction and astronomical lattice, characterized in that, The shale oil sweet spot guiding method includes the following steps: Step 1: Obtain the full-diameter shale or sidewall coring samples of the target block, as well as the logging data of the same well section. The logging data at least includes the natural gamma ray GR curve, resistivity curve, and acoustic travel time curve; Step 2: Conduct controlled experiment processing on the core samples, including conventional pyrolysis analysis, cryogenic pyrolysis analysis with liquid nitrogen, and pyrolysis analysis of the residue after organic solvent extraction, to obtain the original pyrolysis parameters and light hydrocarbon loss; Step 3: Construct a full-component free hydrocarbon recovery model, calculate the cross-layer heavy hydrocarbon amount △S2 and the light hydrocarbon recovery coefficient K, and obtain the corrected full-component true free hydrocarbon. The calculation method is as follows: Step 1: Select representative shale samples, crush them to 80 - 100 mesh, and divide them into three groups: A, B, and C; Step 2: Measure the light hydrocarbon retention and correction coefficient for the samples in group A; Step 3: Perform conventional Rock-Eval pyrolysis on the B group samples and determine the conventional free hydrocarbon S1. 常 And conventional pyrolytic hydrocarbon S2 常 ; Step 4: Perform Soxhlet extraction on the C group samples to remove soluble organic matter until the solvent is colorless. After drying, perform Rock-Eval pyrolysis and determine the residual pyrolysis hydrocarbons S2. 残 ; Step 5: Calculate the relocation of heavy hydrocarbons, and calculate the amount of heavy hydrocarbons that have migrated through the intercalation, ΔS2, where ΔS2 = S2. 常 -S2 残 And based on the coking correction factor α, the content of heavy hydrocarbons S1 after relocation is calculated. 重 =α×△S2; Step 6: Determine the light hydrocarbon recovery coefficient K based on the shale vitrinite reflectance Ro; Step 7: Calculate the corrected true free hydrocarbons of the whole component, and calculate the corrected light hydrocarbon fraction S1. 轻校正 S1 轻校正 =S1 常 ×k, the final total amount of free hydrocarbons in situ, S1 校正 S1 is the sum of the correction amount for light hydrocarbons and the return amount for heavy hydrocarbons. 校正 =S1 轻校正 +S1 重 ; Step 4: Perform detrending and pre-whitening preprocessing on the natural gamma ray logging curve of the entire well section of the target well, and conduct spectral scanning using the multi-taper method MTM to identify the main period of the Milankovitch cycle; Step 5: Use a Gaussian band-pass filter to extract the 405 kyr long eccentricity period signal, establish an astronomical chronostratigraphic framework, and map the corrected total organic carbon TOC and oil saturation index OSI to the astronomical chronostratigraphic framework; Step 6: Based on the corrected geochemical parameters, establish a shale oil sweet spot classification and evaluation standard, and divide into Class I, Class II, and Class III sweet layers; Step 7: Based on the astronomical chronostratigraphic framework and the phase distribution of the sweet layers, guide the horizontal well trajectory design and real-time geological steering.

2. The shale oil sweet spot guidance method based on full-component hydrocarbon correction and astronomical framework according to claim 1, characterized in that, In Step 3, the organic solvent is a mixture of dichloromethane and methanol with a volume ratio of 93:7 to 2:

1. The extraction temperature is set 5 - 10 °C higher than the solvent boiling point, and the extraction time is not less than 72 hours.

3. The method for formation decompaction correction based on software program manual recalculation according to claim 1, characterized in that, The value range of the coke correction coefficient α in Step 3 is 0.65 - 0.

75.

4. The shale oil sweet spot guidance method based on full-component hydrocarbon correction and astronomical framework according to claim 1, characterized in that, The value of the light hydrocarbon recovery coefficient K in Step 3 is as follows: when 0.5% < Ro < 0.7%, K takes a value of 1.09 - 1.16; when 0.7% < Ro < 0.9%, K takes a value of 1.16 - 1.30; when 0.9% < Ro < 1.1%, K takes a value of 1.3 - 1.41; when Ro > 1.1%, K takes a value of 1.41 - 1.

52.

5. The shale oil sweet spot guidance method based on full-component hydrocarbon correction and astronomical framework according to claim 1, characterized in that, The specific parameter settings of the multi-taper method MTM in Step 4 are as follows: Use the discrete prolate spheroidal sequence DPSS as the time window function, set the time-bandwidth product NW to 2 to 4, the frequency resolution of the window function number K is not less than 0.001 cycles / m, and conduct a harmonic F-test on the spectral results based on the multi-taper theory. Only retain the frequency peaks with a confidence level higher than 95% as valid Milankovitch signals.

6. The shale oil sweet spot guidance method based on full-component hydrocarbon correction and astronomical framework according to claim 1, characterized in that, The sweet spot classification and evaluation standard in Step 6 is Class I sweet spot: TOC > 2.0% and the full-component free hydrocarbon content S1 > 6.0 mg / g; Class II sweet spot: 1.0% < TOC < 2.0% and 4.0 < S1 < 6.0 mg / g; Class III sweet spot: TOC < 1.0% or S1 < 4.0 mg / g - 87.

7. The shale oil sweet spot guidance method based on full-component hydrocarbon correction and astronomical framework according to claim 1, characterized in that, In step seven, the real-time geological guidance is as follows: Before drilling, a standard astronomical stratigraphic framework curve based on a 405 kyr period is established using pilot well data. During drilling, real-time natural gamma-ray (LWD-GR) data is acquired. The sliding window correlation comparison method is used to map the drilling data onto the standard astronomical stratigraphic framework in real time, and the current phase angle of the drill bit is calculated. When the drill bit phase deviates from the half-cycle phase interval corresponding to the type I sweet spot, the well inclination angle is adjusted to control the wellbore trajectory to remain within the maximum lacustrine flooding sedimentary section with a short eccentricity period.

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