Method for evaluating abundance of organic matters in hydrocarbon source rock based on element logging

Abstract

The invention relates to a method for evaluating abundance of organic matters in hydrocarbon source rock based on element logging, which comprises the following steps of: S1, analyzing relevancy between element logging and TOC (Total Organic Carbon) content, and selecting an element Y with high relevancy between the content and the TOC content; s2, establishing a correlation curve of the content of the element Y and the content of TOC; and S3, predicting the TOC content according to the actually measured content of the element Y and the correlation curve. According to the method for evaluating the abundance of the organic matters in the hydrocarbon source rock based on the element logging, the problem that the abundance profile of the organic matters of a system cannot be obtained due to the fact that drilling sampling is needed, the sampling amount is small and sampling is discontinuous in the existing method for obtaining the abundance data of the organic matters is solved.

Description

Technical Field

[0001] The present invention relates to the field of geological exploration, and particularly to a method for evaluating the organic matter abundance of source rocks based on element logging. Background Technique

[0002] The Tarim Basin is extremely rich in oil and gas resources, with multiple hydrocarbon-bearing formations, and is a complex superimposed basin. Among them, the high-quality source rocks of the Lower Cambrian Yurtus Formation are widely developed in northern Tarim and are the main source rock layers. The main source rock layers in the platform basin area generally have the characteristics of deep burial, old age, thin strata, multiple hydrocarbon injections, and multiple hydrocarbon accumulations. Multiple sets of reservoir-caprock combinations are developed above the main source rock layer, and the spatial configuration conditions of source-reservoir-caprock are superior. Therefore, studying the organic matter abundance and thickness distribution of the main source rock layer in the platform basin area is of great significance for resource prospects and exploration directions.

[0003] The source rocks of the Yurtus Formation at the bottom of the Cambrian are widely distributed in the northern Tarim area. However, there are few wells drilled through the Yurtus Formation of the Cambrian and even fewer cores taken, making it difficult to establish a source rock development profile based on longitudinally and laterally continuous core samples. Moreover, the source rocks of the Yurtus Formation of the Cambrian are buried deeply, and it is difficult to take cores during drilling, resulting in incomplete or no core samples. Currently, the evaluation research on the organic matter abundance of the source rocks of the Yurtus Formation of the Cambrian is mainly based on profile outcrop samples and a small number of drilling core samples, and it is difficult to obtain a systematic organic matter abundance profile. Summary of the Invention

[0004] The present invention provides a method for evaluating the organic matter abundance of source rocks based on element logging, which overcomes the problems that the existing method for obtaining organic matter abundance data requires drilling sampling, with few samples and discontinuous sampling, resulting in the inability to obtain a systematic organic matter abundance profile.

[0005] The method for evaluating the organic matter abundance of source rocks based on element logging of the present invention includes the following steps:

[0006] S1. Analyze the correlation between element logging and TOC content, and select element Y with a high correlation between its content and TOC content;

[0007] S2. Establish a correlation curve between the content of element Y and TOC content;

[0008] S3. According to the measured content of element Y at a certain depth and the correlation curve, predict the TOC content at the same depth, and the predicted TOC contents at different depths form a TOC content prediction curve.

[0009] Preferably, in step S1, multiple elements Y1, Y2... Ym with a high correlation with TOC content can be selected, and a high correlation means a high absolute value of the correlation coefficient.

[0010] Preferably, in step S3, according to the measured content curves of elements Y1, Y2... Ym respectively and the correlation curves of each element with the TOC content, the TOC content prediction curves corresponding to each element are obtained, where the content measured curve is the curve formed by the content of a certain element at different depths.

[0011] Preferably, in step 3, the average TOC content prediction curve can also be obtained according to the TOC content curves predicted corresponding to the content curves of each element.

[0012] Preferably, in step S1, the element Ya with the highest positive correlation with the TOC content and the element Yb with the highest negative correlation with the TOC content can be selected. Ya and Yb are selected from Y1, Y2... Ym. The first TOC content prediction curve is predicted according to the measured Ya content at different depths, and the second TOC content prediction curve is predicted according to the measured Yb content at different depths.

[0013] Preferably, in step S3, the average value of the TOC content predicted according to the measured Ya content and the TOC content predicted according to the measured Yb content at the same depth is taken, and the average value of the TOC content predicted at different depths forms the average TOC content prediction curve obtained according to the Ya content and the Yb content.

[0014] Preferably, the first TOC content prediction curve is compared with the measured TOC content curve.

[0015] Preferably, the second TOC content prediction curve is compared with the measured TOC content curve.

[0016] Preferably, the average TOC content prediction curve is compared with the measured TOC content value curve.

[0017] Preferably, the element Ya is Si and the element Yb is P.

[0018] Compared with the prior art, the present invention has the following beneficial effects: By the method for evaluating the organic matter abundance of source rocks based on element logging in the present invention, the element logging data is combined with the TOC content, which is the index that can most directly reflect the organic matter abundance, for analysis. The correlation curve between elements and organic matter abundance is established and the organic matter abundance is predicted. The longitudinal profile of the organic matter abundance of Cambrian source rocks is established. By accurately predicting the TOC content, a new basis is provided for the evaluation of Cambrian source rocks under the condition of lacking drilling data. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a schematic flow chart of the method for evaluating the organic matter abundance of source rocks based on element logging in an embodiment of the present invention.

[0020] Figure 2Shown are the logging and element logging characteristics of the Cambrian Yurtus Formation in the Tarim Basin obtained by the method for evaluating the organic matter abundance of source rocks based on element logging according to an embodiment of the present invention.

[0021] Figure 3 Based on the Figure 2 data shown, the correlation curves of Si, P and TOC are established.

[0022] Figure 4 It is Figure 3 a schematic comparison diagram of the predicted curve of TOC content and the measured curve of TOC content. Detailed implementation manners

[0023] The present invention provides a method for evaluating the organic matter abundance of source rocks based on element logging, including the following steps:

[0024] S1. Analyze the correlation between element logging and TOC content in the same facies belt, and select the element Y with a high correlation between its content and TOC content. It can be one element or multiple elements. The TOC (Total Organic Carbon) content is the total organic carbon content, which is a parameter reflecting the organic matter abundance. In this embodiment, Figure 2 the natural gamma (GR) of the DE logging curve of the Cambrian Yurtus Formation rock layer and the element logging data: Si%, Ba%, P%, S% are shown. It can be seen that in the source rock section, the natural gamma value increases and the elements are relatively enriched. At the same time, it can be seen from Figure 2 that the Si element is the element with the highest positive correlation between its content and TOC (the shape of the Si element content curve is closest to the shape of the TOC content curve), and P is the element with the highest negative correlation between its content and TOC content (the Si element content curve and the TOC content curve are negatively correlated). Therefore, in step S1, the Si element and P are selected as two elements with a high correlation between their content and TOC content. In this application, the correlation includes positive correlation and negative correlation, and a high correlation means a high absolute value of the correlation coefficient. The correlation coefficient is a value between -1 and 1, where 0 indicates no correlation, -1 indicates a perfect negative correlation, and 1 indicates a perfect positive correlation. If the correlation coefficient is positive, it means there is a positive correlation between the two variables. If the correlation coefficient is negative, it means there is a negative correlation between them. The correlation coefficient

[0025]

[0026] can be obtained by conventional means in this field. For example, the correlation coefficient between two variables X and Y is calculated by the following formula:

[0027] where n is the number of samples, is the average value of n sample values of the X variable, is the average value of n sample values of the Y variable.

[0028] Figure 2 also shows the index Al content / (Al content + Fe content) that can reflect the sedimentary environment calculated from the element logging data ( Figure 2 expressed as Al / (Al + Fe) in, and the following expressions are similar), Fe content / Ti content, Al content / (Al content + Fe content + Mn content), V content / Ni content, which show obvious different characteristics in the source rocks of the Yurtus Formation. In the source rock section with high organic matter abundance (high TOC content section), the indexes Al content / (Al content + Fe content), Fe content / Ti content, Al content / (Al content + Fe content + Mn content) that reflect whether there is the influence of hydrothermal activity, and the indexes V content / Ni content, S content that reflect the redox environment indicate that submarine hydrothermal activity and upwelling ocean currents provide a large amount of nutrient components for biological reproduction, and the sulfide anoxic environment is conducive to the preservation of organic matter. There is a correlation between element logging and organic matter abundance, which can be used to predict the organic matter abundance.

[0029] S2, establish the correlation curve between the content of element Y and the TOC content. Specifically: in Excel, use the element content as the abscissa and TOC as the ordinate, add a series of data points to make a scatter plot, and then add a trend line (linear), and the formula and R 2 value can be displayed. The R 2 value is the correlation coefficient. In this embodiment, Figure 3 the left figure in shows the correlation curve between the content of Si element and the TOC content, Figure 3 the right figure in shows the correlation curve between the content of P element and the TOC content.

[0030] S3, predict the TOC content according to the measured content of element Y and the correlation curves between the content of Si element and the TOC content. In this embodiment, obtain the first TOC content prediction curve according to the measured content of Si element and the correlation curve between Si element and the TOC content, as Figure 4 shown. Obtain the second TOC content prediction curve according to the measured content of P element and the correlation curve between P element content and the TOC content. The average TOC content prediction curve can also be obtained according to the first TOC content prediction curve and the second TOC content prediction curve. Specifically: obtain the average value of the TOC content predicted according to the content of Si element and the TOC content predicted according to the content of P element at the same position, and connect the average values of the predicted TOC contents at each position to form the average TOC content prediction curve. Compare the three TOC content prediction curves with the measured TOC content values respectively, and it can be determined that the three TOC content prediction curves are very close to the measured TOC content curve. Based on this, it can be considered that the prediction results are very accurate and reliable. In Figure 4Among them, the predicted TOC content is represented by a curve, and the measured TOC content value is represented by a horizontal line. The first TOC content prediction curve, the first TOC content prediction curve, and the average TOC content prediction curve can all reflect the changes in TOC content at different depths.

[0031] Through the method for evaluating the organic matter abundance of source rocks based on element logging of the present invention, the element logging data is combined with the TOC content, which is the index that can most directly reflect the organic matter abundance, for analysis. A correlation curve between elements and organic matter abundance is established to predict the organic matter abundance, and a vertical profile of the organic matter abundance of Cambrian source rocks is established. By more accurately predicting the TOC content, a new basis is provided for the evaluation of Cambrian source rocks under the condition of lacking drilling data.

[0032] The above embodiments are only exemplary embodiments of the present invention and are not used to limit the present invention. The protection scope of the present invention is defined by the claims. Various modifications or equivalent replacements made by those skilled in the art within the essence and protection scope of the present invention also fall within the protection scope of the present invention.

Claims

1. A method for evaluating the organic matter abundance of source rocks based on element logging, characterized in that, Including the following steps: S1. Analyze the correlation between elemental logging and TOC content, and select element Y with a high correlation between its content and TOC content; S2. Establish a correlation curve between the content of element Y and TOC content; S3. Predict the TOC content at the same depth based on the measured content of element Y at a certain depth and the correlation curve, and the TOC content predicted at different depths forms a TOC content prediction curve.

2. The method for evaluating the organic matter abundance of source rocks based on element logging according to claim 1, wherein In step S1, multiple elements Y1, Y2... Ym with a high correlation with TOC content can be selected. A high correlation means a high absolute value of the correlation coefficient.

3. The method for evaluating the organic matter abundance of source rocks based on element logging according to claim 2, wherein In step S3, according to the measured content curves of elements Y1, Y2... Ym respectively and the correlation curves between each element and TOC content, the TOC content prediction curves corresponding to each element are obtained, where the measured content curve is a curve formed by the content of a certain element at different depths.

4. The method for evaluating the organic matter abundance of source rocks based on element logging according to claim 3, wherein In step 3, an average TOC content prediction curve can also be obtained according to the TOC content curves predicted corresponding to the content curves of each element.

5. The method for evaluating the organic matter abundance of source rocks based on element logging according to claim 3, wherein, In step S1, the element Ya with the highest positive correlation with TOC content and the element Yb with the highest negative correlation with TOC content can be selected. Ya and Yb are selected from Y1, Y2... Ym. The first TOC content prediction curve is formed according to the prediction of the measured Ya content, and the second TOC content prediction curve is formed according to the prediction of the measured Yb content.

6. The method for evaluating the organic matter abundance of source rocks based on element logging according to claim 5, wherein, In step S3, the average value of the TOC content predicted based on the measured Ya content and the TOC content predicted based on the measured Yb content at the same depth is taken, and the average value of the TOC content at different depths forms the average TOC content prediction curve obtained based on the Ya content and Yb content.

7. The method for evaluating the organic matter abundance of source rocks based on element logging according to claim 6, wherein Compare the first TOC content prediction curve with the measured TOC content curve.

8. The method for evaluating the organic matter abundance of source rocks based on element logging according to claim 6, characterized in that, Compare the second TOC content prediction curve with the measured TOC content curve.

9. The method for evaluating the organic matter abundance of source rocks based on element logging according to claim 6, wherein Compare the average TOC content prediction curve with the measured TOC content curve.

10. The method for evaluating the organic matter abundance of source rocks based on element logging according to any one of claims 5-9, characterized in that, Element Ya is Si, and element Yb is P.

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