A method for predicting hydrocarbon source rock of Yuer Tusi group in Tarim basin

Abstract

This invention discloses a method for predicting the thickness of source rocks in the Yuertusu Formation of the Tarim Basin. The method involves: S1: Selecting typical wells to determine the lithology and physical properties of the source rocks and their surrounding rocks; S2: Establishing a geological model of source rocks with varying thickness; S3: Performing forward modeling to synthesize seismic profiles; S4: Constructing a quantitative relationship between forward modeling reflection amplitude and source rock thickness; S5: Extracting and normalizing the actual reflection amplitude; and S6: Calculating the source rock thickness. This invention, based on rock physics and combining well and seismic data, predicts the thickness of source rock layers based on the reflection amplitude at the bottom interface of the Yuertusu Formation, offering greater objectivity than conventional methods. This invention can provide thickness distribution information of the Yuertusu Formation source rocks for pre-salt oil and gas exploration in various target areas within the northern Tarim Platform, and also provides a methodological means to solve the problem of predicting thin source rocks in the Tarim Basin.

Description

Technical Field

[0001] This invention relates to the field of seismic exploration and development technology for oil and gas, and in particular to a method for predicting hydrocarbon source rocks in the Yuertu Formation of the Tarim Basin. Background Technology

[0002] Field geological outcrops and drilling data reveal that the mudstone of the Lower Cambrian Yuertu Formation in the Tarim Basin is the highest-quality marine hydrocarbon source rock discovered in China and is also the main hydrocarbon source in the basin. Above it are the Yuertu Formation dolomite limestone, microcrystalline dolomite, and Lower Cambrian Xiaoerbulak Formation dolomite; below it are the Yuertu Formation siliceous rocks and Upper Sinian Qigebulak Formation dolomite.

[0003] Previous studies have utilized extensive data from geological outcrops, core samples, drilling, and geophysical data to conclude that the Yuertusu Formation source rocks are widely deposited in the northern Tarim Basin, with two hydrocarbon generation centers: Manjiaer and Awati-Manxi, respectively designated as the Northern Tarim Basin and the Northern Tarim Platform. Because the Yuertusu Formation source rocks in the Northern Tarim Basin are generally buried at depths exceeding 10,000 meters, exploration wells for Cambrian subsalt dolomite reservoirs in the Tarim Basin are mainly distributed around the uplift zone of the Northern Tarim Platform. The distribution and scale of the Yuertusu Formation source rocks in this area represent a key challenge for deep to ultra-deep Cambrian subsalt oil and gas exploration in the Tarim Basin.

[0004] However, due to the limited research on the Cambrian subsalt strata, except for the Keping fault uplift and the top of the ancient uplift within the basin, the Yuertus Formation mudstone in the Tarim Basin is generally buried at depths exceeding 8000 meters and with a thickness of less than 45 meters. Furthermore, the number of wells encountered is limited, core samples are scarce, and existing seismic data is primarily early 2D data with low resolution, making it impossible to distinguish this mudstone formation. Therefore, the prediction of the Yuertus Formation source rocks remains mainly at the level of seismic and sedimentary facies inference. It relies heavily on indirect estimations of thickness and distribution based on field outcrops, drilling information, tectonic setting, and sedimentary environment, lacking objective and effective prediction methods. Predictions indicate a maximum thickness of several hundred meters, significantly differing from the actual drilled thickness. This uncertainty severely restricts further breakthroughs in subsalt oil and gas exploration in the Tarim Basin. Summary of the Invention

[0005] To address the problem that existing methods cannot accurately predict the thickness and distribution of hydrocarbon source rocks in the Yuertusu Formation of the Tarim Basin, this invention provides a method for predicting the thickness of hydrocarbon source rocks in the Yuertusu Formation of the Tarim Basin, enabling quantitative prediction of the thickness of the Yuertusu Formation source rocks. This invention is based on the rhythmic thin layers formed by the thin, low-impedance mudstone of the Yuertusu Formation and its upper and lower thick, high-impedance limestone, dolomite, and siliceous surrounding rocks. Utilizing the amplitude interference effect of these thin layers, a geological model of variable-thickness mudstone is established, a forward-modeled seismic profile is synthesized, and a quantitative relationship between the thin-layer reflection amplitude and the mudstone thickness is constructed. Furthermore, based on the actual bottom interface of the Yuertusu Formation, i.e. A method for predicting the thickness of argillaceous source rocks in the Yuertu Formation using reflection amplitude.

[0006] This invention provides a method for predicting hydrocarbon source rocks in the Yuertu Formation of the Tarim Basin, comprising the following steps: S1: Select typical wells to determine the lithology and physical properties of the source rocks and their surrounding rocks; S2: Establish a geological model of hydrocarbon source rocks with varying thickness; S3: Perform forward modeling to synthesize seismic profiles; S4: Constructing Forward Model Quantitative relationship between reflection amplitude and source rock thickness; S5: Extraction and Normalization Processing in Practice Reflection amplitude; S6: Calculate the thickness of the source rock.

[0007] Based on the above scheme, step S1 specifically includes: selecting wells in the target area that encounter the Lower Cambrian Xiaoerbulak Formation, Yuertusi Formation argillaceous source rocks and the underlying Sinian Qigebulak Formation, and using drilling data to obtain the lithology and thickness of the formation, and using sonic logging and density logging curves to obtain the layer velocity and density.

[0008] Based on the above scheme, step S2 specifically includes: Range of source rock thickness based on geological outcrop and drilling data; Using the lithology and physical properties of the source rock and its surrounding rocks, a set of strata with constant velocity and density is added above the overlying Xiaoerbulak Formation and below the Xiafuqigebulak Formation to establish a geological model in which the thickness of the source rock layer varies while the thickness of the remaining strata is fixed.

[0009] Based on the above scheme, in step S2, the quantitative relationship between density and sonic transit time is used according to lithological statistics to supplement the locally missing sonic and density data in the selected well.

[0010] Based on the above scheme, in step S3, the minimum phase Ricker wavelet with the same dominant frequency as the actual seismic data is used as the source wavelet, and the self-excited and self-absorbed synthetic seismic profile corresponding to the thickness of the source rock layer is simulated by forward modeling of the acoustic wave equation.

[0011] Based on the above scheme, in step S4, the synthetic seismic profile is extracted. The maximum amplitude of the reflection is normalized, and a normalized forward model is established using a polynomial fitting method. Quantitative relationship between reflection amplitude and source rock thickness.

[0012] Based on the above scheme, step S5 specifically includes: S51: Select two-dimensional or three-dimensional seismic pure wave profiles in the target area, and use a unified amplitude equalization processing method to adjust the amplitude energy of each profile to the same order of magnitude. S52: Explaining and extracting reality The maximum amplitude of the reflection; S53: Two wells in the target area that encountered the Yuertu Formation argillaceous source rocks were selected as known points. The amplitude threshold calculation method under the control of known points was used to obtain the normalized forward model. The critical value of the actual amplitude for reflection amplitude matching; S54: Normalize the actual amplitude based on the threshold to generate the normalized actual amplitude. Reflection amplitude.

[0013] Based on the above scheme, step S6 utilizes normalized forward modeling. The quantitative relationship between reflection amplitude and source rock thickness will be normalized to the actual The reflected amplitude is converted into the thickness of the source rock, generating a source rock thickness distribution map.

[0014] Based on the above scheme, the polynomial fitting is a quadratic polynomial fitting.

[0015] The beneficial effects of this invention are: The method for predicting the thickness of source rocks in the Yuertusu Formation of the Tarim Basin provided by this invention is based on rock physics. It utilizes the interference phenomenon of seismic waves propagating in rhythmic thin layers and the correlation between the interference amplitude and the thin layer thickness. By combining well and seismic data, it predicts the layer thickness based on the reflection amplitude at the bottom interface of the Yuertusu Formation. Compared with existing methods, this method is more objective. When constructing the quantitative relationship between the thin layer interference amplitude and its thickness, this method only considers the thickness of the argillaceous source rocks, ignoring the influence of other factors such as noise, lithological variations of the source rocks, and differences in seismic data acquisition and processing methods at different times on the interference amplitude. Therefore, this method is essentially a quantitative analysis-based method for predicting the thickness of source rocks in the Yuertusu Formation.

[0016] The method of this invention can provide thickness distribution maps of the Yuertu Formation source rocks in various target areas within the Tarim Basin. This can provide a reference for understanding the macroscopic distribution patterns of the Yuertu Formation source rocks, selecting favorable areas for pre-salt oil and gas exploration, and deploying well locations. It also provides a methodological means to solve the problem of predicting thin-thick argillaceous source rocks in the Tarim Basin. Attached Figure Description

[0017] Figure 1 Flowchart of the method for predicting the thickness of source rocks in the Yuertu Formation of the Tarim Basin; Figure 2 Statistical analysis of the quantitative relationship between acoustic transit time and density, and a graph showing the mutual supplementation of missing segments in the curve; Figure 3 Seismic wave velocity and density model for hydrocarbon source rocks with varying thickness; Figure 4 Synthetic seismic profile; Figure 5 Normalized forward modeling Quantitative relationship between reflection amplitude and source rock thickness; Figure 6 Local normalization reality Reflection amplitude distribution diagram; Figure 7 Local thickness distribution map of source rocks. Detailed Implementation

[0018] To make the objectives, advantages and features of the present invention more apparent, the present invention will be further described in detail below with reference to specific embodiments.

[0019] like Figure 1 As shown, this invention provides a method for predicting hydrocarbon source rocks in the Yuertu Formation of the Tarim Basin, specifically including: Step 1: Select a typical well and determine the lithology and physical properties of the source rock and its surrounding rocks.

[0020] Wells were selected in the target area that encountered the Lower Cambrian Xiaoerbulak Formation and Yuertusu Formation argillaceous source rocks and the underlying Sinian Qigebulak Formation, revealing their typical lithological characteristics. Drilling and logging data were used to determine the lithology, thickness, and seismic wave velocity and density of the Yuertusu Formation and its upper and lower surrounding rocks, namely the Cambrian Xiaoerbulak Formation and the Sinian Qigebulak Formation.

[0021] Step 2: Establish a geological model of source rocks with varying thickness.

[0022] Based on field geological outcrops and existing drilling data, the thickness variation range of the Yuertu Formation source rocks was statistically analyzed. Using established stratigraphic thickness and physical property parameters, a set of strata with constant velocity and density was added to the overlying Xiaoerbulak Formation (shallow) and the underlying Sinian Qigebulak Formation (deep), respectively, to establish a geological model with varying source rock thickness and fixed thickness of the remaining strata. This ensured the bottom interface of the Yuertu Formation in the synthetic seismic profile was accurately determined. The reflection has clear reflection characteristics. That is, it is required to have a sufficiently large two-way reflection time, and not be disturbed by the reflection from the bottom interface of the model.

[0023] Among them, the method of quantitatively relating the statistical density and sonic transit time of the selected well lithology is used to supplement the missing sonic and density data of local sections.

[0024] Step 3: Perform forward modeling to synthesize seismic profiles.

[0025] In statistical analysis of actual earthquake data The main frequency of the reflection Select the main frequency as Using the minimum phase Ricker wavelet as the source wavelet, and based on the variable thickness source rock geological model in step 2, the acoustic wave equation forward modeling is used to simulate the self-excited and self-absorbed synthetic seismic profile corresponding to the thickness of the source rock layer.

[0026] Step 4: Construct forward model Quantitative relationship between reflection amplitude and source rock thickness.

[0027] In statistical synthetic seismic profiles The maximum amplitude of the reflection is normalized to a value between 0 and 1. A quadratic polynomial fitting method is then used to fit the normalized forward model. Quantitative relationship between reflection amplitude and source rock thickness.

[0028] Step 5: Extraction and normalization of actual data Reflection amplitude.

[0029] Two-dimensional or three-dimensional pure wave seismic profiles of the target area are selected, and a uniform amplitude equalization method is used to adjust the amplitude energy of each profile to the same order of magnitude. Using the seismic profiles, actual seismic data are interpreted and extracted. The maximum amplitude of the reflection.

[0030] Two wells in the target area that encountered the Yuertu Formation argillaceous source rocks were selected as known points. The normalized forward model of the known points was determined based on the thickness of the source rocks. Reflection amplitude and Combining the actual situation of known points Reflection amplitude and Calculate the upper and lower bounds of the actual amplitude normalization process. and So that the normalized actual amplitude can be in line with the normalized forward model The reflection amplitudes match: ; ; Apply upper and lower bound values and For the actual The amplitude is normalized to generate the normalized actual value. Reflection amplitude.

[0031] Step 6: Calculate the thickness of the source rock.

[0032] Using the quantitative formula in step 4, the normalized actual The reflected amplitude was converted into the source rock thickness. A source rock thickness distribution map was generated using geological mapping software.

[0033] Example 1: Prediction of the thickness of the Yuertu Formation source rocks in the Awati Depression of the Tarim Basin This predictive implementation is based on, as follows Figure 1 Perform the steps shown.

[0034] Step 1: Select a typical well to determine the lithology and physical properties of the source rocks and their surrounding rocks. The KT1(JN) well in the Keping fault uplift was selected, which encountered the Lower Cambrian Xiaoerbulak Formation and Yuertusu Formation argillaceous source rocks and the underlying Sinian Qigebulak Formation in the vicinity of the Awati Depression, and revealed their typical lithological characteristics. Using the drilling and logging data from the KT1(JN) well, the lithology, thickness, and seismic wave velocity and density of the Yuertusu Formation and the upper and lower Xiaoerbulak and Qigebulak Formations were determined.

[0035] Step 2: Establish a geological model of the source rock with varying thickness. The thickness of the source rock is determined to be 0–50 m based on geological outcrops and drilling data in the Awati Depression and its surrounding areas. The quantitative relationship between sonic transit time and density in well KT1 (NJ) is statistically analyzed according to lithology, and missing segments of the sonic or density curves are mutually supplemented. Figure 2 Using the thickness and physical properties of the source rock and its upper and lower surrounding rocks, a set of thick layers with constant velocity and density was added to the shallower Xiaoerbulak Formation and the deeper Qigebulak Formation, respectively, to generate a geological model with a source rock layer thickness ranging from 0 to 50 m in increments of 1 m. Figure 3 ).

[0036] Step 3: Perform forward modeling to synthesize seismic profiles. Determine the dominant frequency of the actual seismic data. Select the main frequency as The minimum phase Ricker wavelet, based on the variable thickness source rock geological model in step 2, is used to simulate the self-excited and self-recovering synthetic seismic profile corresponding to the source rock layer thickness using forward modeling of the acoustic equation. Figure 4 ).

[0037] Step 4: Construct forward model Quantitative relationship between reflection amplitude and source rock thickness. Statistical forward modeling. The maximum reflection amplitude, after normalization, is determined by quadratic polynomial fitting to achieve normalized forward modeling. Quantitative relationship between reflection amplitude and source rock thickness ( Figure 5 ).

[0038] Step 5: Extraction and normalization of actual data Reflection amplitude. Amplitude equalization is uniformly applied to actual two-dimensional or three-dimensional pure-wave seismic data, followed by interpretation and statistical analysis. The maximum reflection amplitude. Taking the XH1 and LT1 wells, which encountered the Yuertu Formation argillaceous source rocks and their upper and lower surrounding rocks in the northeast direction of the Awati Depression and have typical stratigraphic lithological characteristics, as known points, the upper and lower bounds of the actual amplitude normalization process are calculated. After normalization, the generated and normalized forward modeling values ​​are obtained. Actual reflection amplitude matching Reflection amplitude ( Figure 6 ).

[0039] Step 6: Calculate the thickness of the source rock. Using the quantitative formula from Step 4, the actual thickness will be calculated. The reflected amplitude is converted into the source rock thickness, generating a source rock thickness distribution map. Figure 7 ).

[0040] In this embodiment, the actual thickness of the source rock of the Yuertu Formation in the verification well TS5 is 41m, and the predicted thickness is 40m, with a consistency of 97.5%.

[0041] The proposed method for predicting source rocks of the Yuertu Formation in the Tarim Basin is based on the rhythmic thin-layer seismic amplitude interferometry effect. By establishing a quantitative relationship between thin-layer interference amplitude and layer thickness, it directly predicts the thickness of source rocks using seismic amplitude data. Based on rock physics theory, this method can quantitatively predict the thickness of source rocks. This method combines well and seismic data and is implemented under the constraint of existing drilled and exposed thicknesses. The results not only highly match known well data but also ensure the reliability of spatial distribution prediction, making it an objective and effective method. It can provide thickness distribution maps of the Yuertu Formation source rocks in various target areas within the northern Tarim Platform, providing a reference for understanding the macroscopic distribution patterns of the Yuertu Formation source rocks, selecting favorable areas for pre-salt oil and gas exploration, and deploying well locations. It also provides a methodological means to solve the problem of predicting thin-thick argillaceous source rocks in the Tarim Basin.

[0042] The above embodiments have provided a detailed description of the technical solution of the present invention. Obviously, the present invention is not limited to the described embodiments. Based on the embodiments of the present invention, those skilled in the art can make various modifications, but any modifications that are equivalent to or similar to the present invention fall within the scope of protection of the present invention.

[0043] The contents not described in detail in this specification are existing technologies known to those skilled in the art.

Claims

1. A method for predicting hydrocarbon source rocks in the Yuertu Formation of the Tarim Basin, characterized in that, Includes the following steps: S1: Select typical wells to determine the lithology and physical properties of the source rocks and their surrounding rocks; S2: Establish a geological model of hydrocarbon source rocks with varying thickness; S3: Perform forward modeling to synthesize seismic profiles; S4: Constructing Forward Model Quantitative relationship between reflection amplitude and source rock thickness; S5: Extraction and Normalization Processing in Practice Reflection amplitude; S6: Calculate the thickness of the source rock.

2. The method according to claim 1, characterized in that, S1 specifically includes: the selected wells are those that encounter the Lower Cambrian Xiaoerbulak Formation and Yuertusi Formation argillaceous source rocks and the underlying Sinian Qigebulak Formation strata, and the lithology and thickness of the strata are obtained using drilling data, and the layer velocity and density are obtained using sonic and density logging curves.

3. The method according to claim 1 or 2, characterized in that, S2 specifically includes: Range of source rock thickness based on geological outcrop and drilling data; Using the lithology and physical properties of the source rock and its surrounding rocks, a set of strata with constant velocity and density is added above the overlying Xiaoerbulak Formation and below the Xiafuqigebulak Formation to establish a geological model in which the thickness of the source rock layer varies while the thickness of the remaining strata is fixed.

4. The method according to claim 3, characterized in that, In S2, the quantitative relationship between density and sonic transit time is used based on lithological statistics to supplement the locally missing sonic and density data in the selected well.

5. The method according to claim 1, characterized in that, In S3, the minimum-phase Rick wavelet with the same dominant frequency as the actual seismic data is used as the source wavelet, and the self-excited and self-absorbed synthetic seismic profile corresponding to the thickness of the source rock layer is simulated by forward modeling of the acoustic equation.

6. The method according to claim 1, characterized in that, In step S4, the synthetic seismic profile is extracted. The maximum amplitude of the reflection is normalized, and a normalized forward model is established using a polynomial fitting method. Quantitative relationship between reflection amplitude and source rock thickness.

7. The method according to claim 1, characterized in that, S5 specifically includes: S51: Select two-dimensional or three-dimensional seismic pure wave profiles in the target area, and use a unified amplitude equalization processing method to adjust the amplitude energy of each profile to the same order of magnitude. S52: Explaining and extracting reality The maximum amplitude of the reflection; S53: Two wells in the target area that encountered the Yuertu Formation argillaceous source rocks were selected as known points. The amplitude threshold calculation method under the control of known points was used to obtain the normalized forward model. The critical value of the actual amplitude for reflection amplitude matching; S54: Normalize the actual amplitude based on the threshold to generate the normalized actual amplitude. Reflection amplitude.

8. The method according to claim 1, characterized in that, S6 utilizes normalized forward modeling. The quantitative relationship between reflection amplitude and source rock thickness will be normalized to the actual The reflected amplitude is converted into the thickness of the source rock, generating a source rock thickness distribution map.

9. The method according to claim 6, characterized in that, The polynomial fitting is a quadratic polynomial fitting.

Images