CN104700316B - A method for evaluating oil and gas generation of shale by heterogeneity - Google Patents

Abstract

The invention relates to a method for evaluating the oil and gas generation capacity of mud shale by heterogeneity, which comprises the following steps: 1. Intensively sampling points at different depths on the mud shale profile, and obtaining basic parameter values through Rock-Eval pyrolysis detection, Determine the type of organic matter; 2. Establish a conceptual model and calculate the content of organic carbon in different forms; 3. Design simulation experiments to establish the evolution model of heavy hydrocarbon oil yield and natural gas yield. 4. Calculate the total hydrocarbons generated and discharged at different depth points of shale, as well as the amount of heavy oil, light oil and gas, and evaluate the heterogeneity of oil and gas content of shale. The model of the present invention is based on a large number of sample data points in the profile, and can evaluate the heterogeneity of mud shale oil and gas resources. When the samples are limited, the present invention is still applicable in combination with logging data, so it is useful for quantitatively characterizing mud shale It is of great significance to understand the heterogeneity of oil and gas bearing properties of rocks and to accurately evaluate unconventional shale oil and gas resources.

Description

A method for evaluating oil and gas generation of shale by heterogeneity

technical field

The invention belongs to the technical field of oil and gas exploration and development, and in particular relates to a method for evaluating the amount of oil and gas generated by mud shale.

Background technique

Due to rising energy demand and increasing energy pressure, shale oil and gas, an unconventional energy source, has received more and more attention. The United States is at the forefront of the world in the exploration and development of mud shale, and is currently the only country that has successfully achieved large-scale commercial development of mud shale gas. In 1976, the U.S. Department of Energy began to pay attention to shale gas in the east, and carried out research on shale gas geology, geochemistry and Research in Petroleum Engineering (Curtis, 2002). Canada followed suit, and in recent years has also carried out shale gas exploration and experimental research, evaluating the exploration potential of Devonian, Carboniferous and Jurassic shale gas (Ross D & Bustin, 2007, 2008).

In the composition of natural gas resources in China, coal-measure source rocks and marine carbonate rocks make a greater contribution, and domestic researchers and explorers pay more attention to shale gas in the Paleozoic marine and coal-measure shale in western and southern China. Formation and exploration potential of rock gas (Zhang Jinchuan et al., 2003, 2004, 2007, 2008, 2009; Zhang Shuichang et al., 2006; Liang Digang et al., 2008; Ye Jun et al., 2008; Nie Haikuan et al., 2009, 2010, 2011; Zhu Hua et al. , 2009; Wang Lansheng et al., 2009; Wang Shiqian et al., 2009; Xu Shilin et al., 2009; Cheng Keming et al., 2009; Huang Jizhong et al., 2009; Pu Boling et al., 2008, 2010; ; Chen Shangbin et al., 2011; Liang Xing et al., 2011; Wang Shejiao et al., 2011); the proportion of natural gas generated from lacustrine source rocks is relatively small, and shale oil and gas exploration from lacustrine source rocks in eastern China is more popular in China. is in its infancy. Lacustrine source rocks are the main hydrocarbon-generating material basis of China's oil and gas resources, and their contribution to natural gas resources is very asymmetrical. The main reason is that most lake basins in China have relatively shallow burials and have not entered the threshold of high-maturity gas formation. However, lacustrine basins in eastern China are very oil-rich. Taking the Paleogene in the Dongying sag as an example, it is a typical oil-rich lacustrine basin, in which a large set of mud shale developed, forming a relatively closed system in which a large amount of hydrocarbons remained. Therefore, abundant unconventional shale oil and gas resources can be formed.

The amount of oil and gas resources in shale is that solid organic matter is transformed into liquid or gaseous hydrocarbons through thermal evolution and stored in the pores of shale. amount of hydrocarbon generation), hydrocarbon generation amount (the amount of hydrocarbons that have been generated so far), hydrocarbon expulsion amount (the amount of hydrocarbons generated and expelled from its own rocks), and hydrocarbon expulsion coefficient (the ratio of hydrocarbon expulsion amount to hydrocarbon generation amount), these parameters All determinations are related to the organic carbon content in the shale. Due to the serious heterogeneity of source rocks in faulted continental lacustrine basins, manifested as the heterogeneity of organic matter distribution and the unbalanced compaction of source rocks, the generation and discharge of hydrocarbons in source rocks are usually It is not uniform and continuous, which leads to the heterogeneity of the distribution of oil and gas resources in the shale system.

The basic standards for enrichment and recoverability of shale oil and gas in North America, where shale oil and gas have been successfully explored and developed in the world, are: higher abundance of organic matter, higher maturity, better type of organic matter, and higher content of brittle minerals ( low content of clay minerals). However, in my country's continental basins, especially the faulted basins in the east, sedimentary facies changes frequently, and the distribution of organic matter in shale is highly heterogeneous. Therefore, it is necessary to have a set of highly operable and effective evaluation methods for the mud shale oil and gas resources with lacustrine characteristics in China.

At present, the quantitative evaluation methods of hydrocarbon generation proposed and applied by China National Petroleum Corporation and research institutes can be summarized into three categories: 1. Improved chloroform asphalt method; 2. Hydrocarbon generation based on the mechanism of organic matter hydrocarbon generation Rate method (thermal simulation experiment method, chemical kinetic method, material balance method); 3. Hydrocarbon generation potential index method. However, the existing evaluation methods for shale oil and gas resources still have the following shortcomings or problems:

(1) The existing method mostly calculates the amount of hydrocarbon generation based on the current measured organic carbon content, but the current measured organic carbon content is actually the residual organic carbon content after hydrocarbon generation, and the organic carbon content predicted by well logging information is actually Residual organic carbon content; based on the fact that the generation of oil and gas is determined by the converted organic carbon, the converted organic carbon is converted into hydrocarbons and discharged to form oil and gas resources, so different forms of organic carbon (such as original organic carbon content, discharged Organic carbon content, etc.) is also very important to accurately evaluate shale oil and gas resources, and the existing methods cannot meet the new needs.

(2) The existing evaluation parameters of shale hydrocarbon generation are very limited, usually based on chloroform bitumen “A”, residual hydrocarbon generation potential S1+S2, and residual organic carbon content TOC, because these parameters can be directly detected , no calculation is required. Most of the estimated few parameters are the amount of hydrocarbon generation Q, which is often estimated by the volumetric method. Therefore, limited parameters cannot satisfy the accurate evaluation of shale oil and gas resources.

(3) The existing evaluation of shale oil and gas resources usually evaluates shale gas. This is because the evaluation areas such as North America and western China have high maturity, almost all of them are gas, and the amount of oil is very small. ; In recent years, shale oil in mutual basins in eastern China has also gradually received attention. However, these evaluation ideas can not meet the needs. For example, the deep layers of Paleogene in the Dongying Sag, Bohai Bay Basin, East China have relatively good conditions for the formation of lacustrine shale gas. In this sag, the source rocks of the upper submember of the fourth member of the Shahejie Formation and the lower submember of the third member of the Shahejie Formation are developed. Some natural gas is also generated along with oil, so how to evaluate shale oil and gas at the same time is a very important issue. Moreover, in the existing oil and gas evaluation, heavy oil and light oil (C6-C13 light hydrocarbons) are not separated, because light oil is easy to leak during detection.

(4) Most of the existing research work on hydrocarbon generation evaluation of shale is limited to geochemical testing and analysis of limited sampling points of source rocks. The important reason is that the successful exploration and development of shale oil and gas in North America is basically in relatively uniform marine strata, with small facies change and strong homogeneity, and shale oil and gas can basically be determined using limited laboratory analysis data. Favorable development areas and spatial development of oil and gas. However, due to the serious heterogeneity of continental mud shale and the complexity of hydrocarbon generation and expulsion problems, limited sampling test points cannot objectively reflect the complex geological conditions, and it is even more difficult to effectively analyze the vertically continuous distribution of mud shale. High-resolution evaluation of shale also makes it difficult to identify thin-layer high-quality mud shale with high organic matter content and high hydrocarbon generation and expulsion efficiency in thick source rocks, which affects exploration deployment, such as which resources can be effectively exploited in the near future What resources can be effectively exploited as prospective resources wait for technological progress, and which resources have no economic value, thus hindering the progress of oil and gas evaluation and exploration. In addition, the evaluation based on the actual measurement data of the sample has the characteristics of expensive measurement method and high cost.

In summary, although important progress has been made in the evaluation of unconventional shale oil and gas resources, it is still necessary to comprehensively evaluate different types of organic carbon and multi-parameter oil and gas components (heavy oil, light oil and natural gas) in shale. Looking forward to solving. In particular, evaluating the heterogeneity of shale oil and gas generation with high resolution and guiding the exploration of shale oil and gas is an important development direction for future research on shale oil and gas resources.

Contents of the invention

Aiming at the above-mentioned deficiencies existing in the evaluation of the existing mud shale oil and gas resources, the present invention provides a method for heterogeneity evaluation of mud shale oil and gas generation. The method evaluates the heterogeneity of mud shale oil and gas resources, It is of great significance to quantitatively characterize the heterogeneity of shale oil and gas and accurately evaluate unconventional shale oil and gas resources.

The technical solution of the present invention is: a method for evaluating the oil and gas generation capacity of mud shale by heterogeneity, comprising the following steps:

1. Intensively sample different depth points on the shale profile, and obtain basic parameter values through Rock-Eval pyrolysis detection to determine the type of organic matter: Sampling is carried out at a sample point every 1-10m in the depth direction of the shale profile. The collected samples were analyzed by Rock-Eval pyrolysis, and the parameter values of the basic parameters were obtained through Rock-Eval pyrolysis; the hydrogen index HI, the yield index PI and the hydrocarbon index [100× S ₁ ]/TOC, S ₁ is the free hydrocarbons obtained by pyrolysis of rocks at low temperature in the Rock-Eval stage, TOC is the actually detected organic carbon, and the type of organic matter is determined by the hydrogen index HI and basic parameters.

2. Establish a conceptual model and calculate the content of organic carbon in different forms: According to the composition and transformation principles of organic carbon, the organic carbon in mud shale is divided into a conceptual model of different forms of organic carbon, and organic carbon is defined as residual organic carbon, residual effective Carbon, residual ineffective carbon, excreted organic carbon, expelled effective carbon, original organic carbon, original effective carbon, original ineffective carbon, total original organic carbon TOC in mud _shale includes both expelled organic carbon TOC _Exp and residual organic carbon TOC _Rem part, then there is a relationship as shown in formula (1), in the original organic carbon TOC ₀ , the organic carbon part converted into hydrocarbons by pyrolysis is defined as the effective carbon TOC _rea , and the effective carbon contained in the original organic carbon TOC ₀ and the effective carbon in residual organic carbon TOC _Rem are defined as TOC _0-rea and TOC _Rem-rea respectively; the residual hydrocarbon generation potential in mud shale is converted from effective carbon in residual organic carbon, which is related to residual organic carbon The relational expression that the residual degradation rate D _Rem of TOC _Rem exists is as shown in formula (2); The expressions of described formula (1) and formula (2) are as follows:

TOC ₀ = TOC _Rem +TOC _Exp (1)

D _Rem = TOC _Rem-rea /TOC _Rem (2)

At present, 0.083 is regarded as the conversion coefficient of carbon into hydrocarbons in the petroleum industry, then there is a relational expression as shown in formula (3), and the expression of formula (3) is as follows:

TOC _Rem-rea = (S ₁ +S ₂ )×0.083(3) In the formula, S ₂ is the pyrolyzed hydrocarbon obtained from rock Rock-Eval high temperature stage pyrolysis,

Then the residual degradation rate D _Rem is calculated by the formula (4), and the expression of the formula (4) is as follows:

D _Rem = (S ₁ +S ₂ )×0.083/TOC _Rem (4)

The original degradation potential of different organic matter was determined according to the intersection plot of residual degradation rate D _Rem and pyrolysis peak temperature T _max ;

In the process of organic matter evolution and hydrocarbon formation, the invalid carbon in it can be considered as constant, therefore, there is a relationship as shown in formula (5), and the expression of formula (5) is as follows:

TOC ₀ (1–D ₀ )=TOC _Rem (1–D _Rem )(5)

In the formula (5), TOC ₀ (1–D ₀ ) represents the invalid carbon in the original organic matter, defined as TOC _Ine , and TOC _Rem (1–D _Rem ) represents the invalid carbon in the residual organic matter, defined as TOC _{Rem- Ine} ;

Formula (5) can be transformed into formula (6) and formula (7), and the expressions of formula (6) and formula (7) are as follows:

(1–D _Rem )/(1–D ₀ )＝TOC ₀ /TOC _Rem (6)

R _C =TOC ₀ /TOC _Rem (7)

In the formula (7), R _C is the recovery coefficient from the residual organic carbon to the original organic carbon measured today, which is a constant coefficient and has no unit;

At the same time, there is also a relational expression as shown in formula (8), and the expression of formula (8) is as follows:

TOC ₀ -TOC _0-rea = TOC _Rem -TOC _Rem-rea (8)

In the formula (8), TOC ₀ -TOC _0-rea represents the invalid carbon in the original organic matter, which is defined as TOC _0-Ine , and TOC _Rem -TOC _Rem-rea represents the invalid carbon in the residual organic matter, which is defined as TOC _{Rem- Ine} ;

Calculate the residual degradation rate D _Rem of each sample point, the original organic carbon recovery coefficient R _C and the heterogeneity distribution of each form of organic carbon content in the profile through the above formula, and provide basic data for the evaluation of shale oil and gas resources ;

3. Design simulation experiments and establish heavy hydrocarbon oil yield and natural gas yield evolution models: select mud shale samples for thermal evolution simulation experiments to obtain hydrocarbon yield curves, establish heavy oil yield and natural gas yield evolution models, and establish The measured maturity parameter vitrinite reflectance VR _o varies with depth.

4. Calculate the total hydrocarbons generated and discharged at different depth points of shale, as well as the amount of heavy oil, light oil and gas, and evaluate the heterogeneity of oil and gas content of shale: according to step 1 and For each parameter obtained in step 2, calculate the total hydrocarbon generation S _Gen and hydrocarbon expulsion S _Exp of each shale sample point; calculate the oil and gas generation of each depth point sample according to the model established in step 3, On the basis of obtaining heavy oil and natural gas yields, further obtain C ₆ ~C ₁₄ light oil yields; and then obtain heavy oil yields S _ho , light oil yields S _lo , natural gas The distribution of the yield S _g is used to quantitatively evaluate the heterogeneity of heavy oil, light oil and gas-bearing properties in shale; through the above parameters obtained, the evaluation parameter profile of shale hydrocarbon generation is established, and the Evaluation of profile distribution heterogeneity of shale oil and gas resources by parameter profiles.

Preferably, in step 1, the basic parameters include measured residual organic carbon TOC _Rem , free hydrocarbons S ₁ obtained by pyrolysis of rock Rock-Eval low temperature stage, and pyrolyzed hydrocarbon S obtained by rock Rock-Eval high temperature stage pyrolysis ₂ and the pyrolysis peak temperature T _max , where the pyrolysis peak temperature T _max is the peak value corresponding to the pyrolysis hydrocarbon S ₂ obtained from the pyrolysis of the rock Rock-Eval high temperature stage, and the measured residual organic carbon TOC _Rem is the current actual detection of the sample The organic carbon TOC obtained; the hydrogen index HI indicates the hydrocarbon generation potential of the mud shale, and the productivity index PI indicates the maturity and thermal evolution of the mud shale, and the organic matter is determined by the intersection graph of the hydrogen index HI and the pyrolysis peak temperature T _max Types of.

As a preference, in the step 3, select representative large homogeneous mudstone samples, divide them into 9 parts and put them into the heating tank respectively, and do thermal evolution simulation experiments; 9 parts of samples are respectively heated from The experimental temperature is raised from room temperature to 250°C, 300°C, 350°C, 400°C, 450°C, 500°C, 550°C, 600°C, and 650°C. When each sample reaches its own end point temperature, use a constant The speed and constant flow pump injected distilled water at a rate of 2ml/min to take out the discharged oil and gas products in time, and collected and measured the oil and gas products obtained from the thermal simulation experiment of each sample.

As a preference, in step 3, the heavy oil yield and natural gas yield evolution models are shown in formula (9) and formula (10), and the expressions of formula (9) and formula (10) are as follows:

Heavy oil yield per unit of organic matter＝440.93VR _o ³ -1629VR _o ² +2053.3VR _o -618.7(9)

Unit organic matter natural gas yield = 18.371VR _o ³ +45.684VR _o ² -62.693VR _o +28.05(10)

In the formula, VR _o is the maturity parameter vitrinite reflectance.

As a preference, in step 3, the measured maturity parameter vitrinite reflectance VR _o varies with depth as shown in formula (11), and the expression of formula (11) is as follows:

VR _o =0.1605e ^0.535H (11)

In the formula, H is the burial depth of the sample point in m.

Preferably, in step 4, the original hydrocarbon generation potential S _OP and hydrocarbon expulsion coefficient K _P are also calculated according to the parameters obtained in step 1 and step 2, the original hydrocarbon generation potential S _OP , the amount of hydrocarbon generation S _Gen , the hydrocarbon expulsion coefficient The calculation formulas of the amount S _Exp and the hydrocarbon expulsion coefficient K _P are shown in formulas (12), (13), (14), and (15), and the expressions of formulas (12), (13), (14), and (15) The formula is as follows:

S _OP =TOC ₀ ×D ₀ /0.083(12)

S _Exp = S _OP - (S ₁ +S ₂ )(13)

S _Gen = S _OP - S ₂ (14)

K _P = S _Exp / S _Gen × 100% (15)

In the formula, TOC ₀ is the original organic carbon, D ₀ is the original degradation rate, and S ₁ is the free organic carbon obtained by pyrolysis in the rock-Eval low temperature stage.

The free hydrocarbons and S ₂ are the pyrolyzed hydrocarbons obtained from the pyrolysis of rocks in the high temperature stage of Rock-Eval.

As a preference, in step 4, the oil and gas production amount of samples at each depth point is calculated by formula (16) and formula (17), and the expressions of formula (16) and formula (17) are as follows:

Production amount of heavy oil per unit sample = yield of heavy oil per unit of organic matter × TOC(16)

The amount of natural gas generated per unit sample = □ organic □ natural gas yield × TOC (17).

As preferably, in step 4, the yield of light oil is obtained by subtracting the yield of pyrolysis hydrocarbon as shown in formula (18), and the expression of formula (18) is as follows:

S _lo = S _Gen - S _ho - S _g (18)

In the formula, S _lo is the light oil yield, S _Gen is the original hydrocarbon generation potential of the sample, S _ho is the heavy oil yield, and S _g is the natural gas yield.

The beneficial effects of the present invention are: (1) the present invention establishes the conceptual model of different organic carbon forms for the first time, and organic carbon is divided into residual organic carbon, residual effective carbon, residual ineffective carbon, discharged organic carbon, discharged effective carbon, original organic carbon , original effective carbon, original invalid carbon, and established a method model, which can calculate these various forms of organic carbon content; the present invention can calculate each evaluation parameter of heterogeneity evaluation mud shale resources by establishing a model, Including the original hydrocarbon generation potential S _OP , the amount of hydrocarbon generation S _Gen , the amount of hydrocarbon expulsion S _Exp and the coefficient of hydrocarbon expulsion K _P , etc.; the present invention also combines the oil and gas yield models of oil and gas in mud shale to further calculate the mud sheet The amount of heavy oil, light oil and natural gas in rocks; different from conventional oil and gas resource evaluation, which uses source rock volume averaging method to estimate, this method model is established on each sample point, and can be used for mud The heterogeneity evaluation of shale oil and gas resources is of great significance to quantitatively characterize the heterogeneity of shale oil and gas and to accurately evaluate unconventional shale oil and gas resources. (2) This program evaluates shale oil and gas resources through a set of overall parameters, such as original organic carbon content, original hydrocarbon generation potential, hydrocarbon generation amount, hydrocarbon expulsion amount, hydrocarbon expulsion coefficient, heavy oil yield, light Quality oil yield, natural gas yield, the evaluation method of the present invention has significant progress compared with previous simple evaluation mud shale hydrocarbon generation amount, or oil generation amount, or gas generation amount. (3) This method can simultaneously calculate points at different depths in a large vertical set of shale, and can evaluate the heterogeneity distribution of shale oil and gas resources in the vertical direction. Other techniques are aimed at single or limited The samples were observed and could not reflect the heterogeneity of the shale. (4) This method is easy to operate, feasible, and low in cost. The data come from the residual organic carbon content provided by Rock-Eval pyrolysis, free hydrocarbon S ₁ , pyrolysis hydrocarbon S ₂ , pyrolysis peak temperature T _max , and oil and gas The productivity model can be used for calculation; if the samples are limited, the residual organic carbon content can be predicted by using the density logging, acoustic logging, and resistivity logging information, and the relationship between TOC _Rem and S ₂ and S ₁ can be established based on the limited measured samples. In this way, the corresponding S ₂ , S ₁ , and Tmax values can be calculated based on the TOC _Rem value predicted by the logging data and the correlation model, and the calculation of the whole set of methods can be completed to realize the industrial mud Overall evaluation of shale oil and gas resources.

Description of drawings

Accompanying drawing 1 is the TOC _Rem , S ₁ , S ₂ and T _max values obtained by Rock-Eval pyrolysis in a specific embodiment of the present invention.

Accompanying drawing 2 is the hydrogen index HI, the yield index PI and the hydrocarbon index [100×S ₁ ]/TOC of each deep sample point determined by calculation in a specific embodiment of the present invention.

Accompanying drawing 3 is the intersection chart of hydrogen index HI and pyrolysis peak temperature T _max of the specific embodiment of the present invention.

Accompanying drawing 4 is the concept model of different forms of organic carbon division of the specific embodiment of the present invention.

Accompanying drawing 5 is the schematic diagram of the division of the form of organic carbon and the relationship model of the specific embodiment of the present invention.

Accompanying drawing 6 is the intersection chart of residual degradation rate D _Rem and pyrolysis peak temperature T _max of the specific embodiment of the present invention.

Accompanying drawing 7 is the profile distribution figure of various forms of organic carbon content of specific embodiment of the present invention.

Accompanying drawing 8 is the sectional view of the evaluation parameters of mud shale hydrocarbon generation according to the specific embodiment of the present invention.

Accompanying drawing 9 is the evolution model of heavy oil yield and natural gas yield obtained from the thermal evolution simulation experiment of the specific embodiment of the present invention.

Figure 10 is a distribution diagram of heavy oil yield S _ho , light oil yield S _lo , and natural gas yield S _g for each unit sample point in a specific embodiment of the present invention.

Accompanying drawing 11 is the variation model of the crude oil cracking gas production rate obtained from the crude oil cracking gas simulation experiment of the specific embodiment of the present invention.

Accompanying drawing ₁₂ is the distribution model of segmental correlation between S2 and TOC _Rem measured in Paleogene in Dongying depression according to a specific embodiment of the present invention.

Accompanying drawing 13 is the distribution model of segmental correlation between S ₁ +S ₂ and TOC _Rem measured in Paleogene in Dongying sag according to a specific embodiment of the present invention.

Accompanying drawing 14 is the flow chart diagram of the specific embodiment of the present invention.

In the figure, TOC _Rem : residual organic carbon measured in the current sample, in %; TOC ₀ : original organic carbon; TOC _Exp : exhausted organic carbon, in %; TOC _Rea : effective carbon converted into hydrocarbons by pyrolysis, in unit TOC _0-rea : original effective carbon, unit is %; TOC _Rem-rea : residual effective carbon, unit is %; TOC _Ine : invalid carbon that cannot be pyrolyzed into hydrocarbons, unit is %; TOC ₀ -rea _ine : original ineffective carbon, in %; TOC _Rem-ine : residual ineffective carbon, in %.

detailed description

The present invention will be further described below in conjunction with accompanying drawing.

In this example, the third member of Paleogene Shahejie Formation in Well N38 in Dongying, Bohai Bay Basin was taken as an example to evaluate the heterogeneity of oil and gas generation in mud shale.

As shown in Fig. 14, a heterogeneity method for evaluating oil and gas generation of shale includes the following steps:

1. Intensively sample different depth points on the shale profile, and obtain basic parameter values through Rock-Eval pyrolysis detection to determine the type of organic matter.

On the shale profile, samples are taken every 1-10m in the depth direction, and the collected samples are analyzed by Rock-Eval pyrolysis, and the parameter values of basic parameters are obtained through Rock-Eval pyrolysis. In this example, the basic parameters include the measured residual organic carbon TOC _Rem , free hydrocarbons S ₁ obtained from rock Rock-Eval low-temperature pyrolysis, pyrolyzed hydrocarbons S ₂ obtained from rock Rock-Eval high-temperature pyrolysis, and The pyrolysis peak temperature T _max , where the pyrolysis peak temperature T _max is the peak value corresponding to the pyrolysis hydrocarbon S2 obtained by the pyrolysis of the rock Rock _- Eval high temperature stage, and the measured residual organic carbon TOC _Rem is actually detected by the samples today Organic carbon TOC, as shown in Figure 1, is the parameter values of the basic parameters TOC _Rem , S ₁ , S ₂ and T _max obtained by Rock-Eval pyrolysis. Determine the hydrogen index HI, yield index PI, and hydrocarbon index [100×S ₁ ]/TOC of each deep sample point according to the basic parameters, as shown in Figure 2. The index PI and the hydrocarbon index [100×S ₁ ]/TOC, where the hydrogen index HI indicates the hydrocarbon generation potential of the shale, and the productivity index PI indicates the maturity and thermal evolution of the shale. As shown in Figure 3, the intersection graph of the index HI and the pyrolysis peak temperature T _max is used to determine the type of organic matter through the intersection graph of the hydrogen index HI and the pyrolysis peak temperature T _max . Type, Type II1, Type II2 and Type III. In actual operation, the organic matter type of each sample point in Figure 1 and Figure 2 is determined through Figure 3.

2. Establish a conceptual model and calculate the content of different forms of organic carbon.

According to the composition and transformation principle of organic carbon, the conceptual model of organic carbon in mud shale is divided into different organic carbon forms, as shown in Figure 4. Available carbon, residual invalid carbon, expelled organic carbon, expelled available carbon, original organic carbon, original available carbon, original ineffective carbon, total original organic carbon TOC in mud shale ₀ includes expelled organic carbon TOC _Exp and residual organic carbon TOC _Rem If there are two parts, there is a relationship as shown in formula (1). In the original organic carbon TOC ₀ , the part of organic carbon converted into hydrocarbons by pyrolysis is defined as the effective carbon TOC _rea , and the effective carbon contained in the original organic carbon TOC ₀ Carbon and residual organic carbon The effective carbon in TOC _Rem is defined as TOC _0-rea and TOC _Rem-rea , respectively. Figure 5 is a schematic diagram of the division and relationship model of organic carbon.

The expression of described formula (1) is as follows:

TOC ₀ = TOC _Rem +TOC _Exp (1)

With the increase of maturity, the original organic carbon will be gradually converted into hydrocarbons, the content of discharged organic carbon will gradually increase, and the content of residual organic carbon will gradually decrease. When the maturity of organic matter reaches the threshold of oil generation (ie vitrinite reflectance R _o =0.5%), the available carbon will start to be converted into hydrocarbons, and the invalid carbon will not be converted into hydrocarbons no matter how much heat is applied.

The residual hydrocarbon generation potential in mud shale is converted from the available carbon in the residual organic carbon, and the relationship between it and the residual degradation rate D _Rem of residual organic carbon TOC _Rem is shown in formula (2); formula (2 ) is expressed as follows:

D _Rem = TOC _Rem-rea /TOC _Rem (2)

At present, 0.083 is regarded as the conversion coefficient of carbon into hydrocarbons in the petroleum industry, then there is a relational expression as shown in formula (3), and the expression of formula (3) is as follows:

TOC _Rem-rea = (S ₁ +S ₂ )×0.083(3)

Then the residual degradation rate D _Rem is calculated by the formula (4), and the expression of the formula (4) is as follows:

D _Rem = (S ₁ +S ₂ )×0.083/TOC _Rem (4)

Figure 6 shows the intersection graph of the residual degradation rate D _Rem and the pyrolysis peak temperature T _max , and the original degradation rate D ₀ of different organic matter is determined according to the intersection graph of the residual degradation rate D _Rem and the pyrolysis peak temperature T _max .

The original degradation rate D ₀ is determined by the residual degradation rate D _Rem of different types of organic matter, that is to say, the original degradation rate D ₀ is the maximum degradation rate when the maturity of organic matter is very low. It can be determined from Fig. 6 that the original degradation rates _D0 of III, II2, III1 and I are 0.15, 0.35, 0.55 and 0.65, respectively.

In the process of organic matter evolution and hydrocarbon formation, the invalid carbon in it can be considered as constant, therefore, there is a relationship as shown in formula (5), and the expression of formula (5) is as follows:

TOC ₀ (1–D ₀ )=TOC _Rem (1–D _Rem )(5)

In the formula (5), TOC ₀ (1–D ₀ ) represents the invalid carbon in the original organic matter, defined as TOC _Ine , and TOC _Rem (1–D _Rem ) represents the invalid carbon in the residual organic matter, defined as TOC _{Rem- Ine} .

Formula (5) can be transformed into formula (6) and formula (7), and the expressions of formula (6) and formula (7) are as follows:

(1–D _Rem )/(1–D ₀ )＝TOC ₀ /TOC _Rem (6)

R _C =TOC ₀ /TOC _Rem (7)

In the formula (7), R _C is the recovery coefficient from the residual organic carbon to the original organic carbon measured today, which is a constant coefficient and has no unit.

At the same time, there is also a relational expression as shown in formula (8), and the expression of formula (8) is as follows:

TOC ₀ -TOC _0-rea = TOC _Rem -TOC _Rem-rea (8)

In the formula (8), TOC ₀ -TOC _0-rea represents the invalid carbon in the original organic matter, which is defined as TOC _0-Ine , and TOC _Rem -TOC _Rem-rea represents the invalid carbon in the residual organic matter, which is defined as TOC _{Rem- Ine} .

Calculate the residual degradation rate D _Rem of each sample point, the original organic carbon recovery coefficient R _C and the heterogeneity distribution of each form of organic carbon content in the profile through the above formula, and provide basic data for the evaluation of shale oil and gas resources , as shown in Figure 7, is the profile distribution diagram of various forms of organic carbon content.

3. Design simulation experiments and establish evolution models of heavy hydrocarbon oil yield and natural gas yield.

Select a representative large homogeneous mudstone sample, divide it into 9 parts and put them into the heating tank for thermal evolution simulation experiment; the 9 samples are raised from the experimental temperature from room temperature to 250 °C, 250 °C, 9 end temperatures of 300°C, 350°C, 400°C, 450°C, 500°C, 550°C, 600°C, and 650°C. When each sample reaches its end point temperature, use a constant-speed constant-flow pump at 2ml/min Inject distilled water at a high rate to take out the discharged oil and gas products in time, collect and measure the oil and gas products obtained from the thermal simulation experiment of each sample, and obtain the hydrocarbon yield curve. The simulated products are divided into three categories according to molecular weight and physical properties. One is heavy oil with relatively large molecules (that is, chloroform bitumen "A" + discharged heavy oil), which can be obtained directly; the other is gas with small molecules (C ₁ ~C ₅ ), which can also be obtained directly; the third is light oil of C ₆ ~C ₁₄ which is volatile at room temperature, which is not easy to collect in experiments. Based on the detected heavy oil and gas, the yield characteristics of light oil can be analyzed by means of mutual compensation. The experimental temperature in the experiment can be converted into the maturity parameter vitrinite reflectance VR _o according to the burial history, thermal evolution model and hydrocarbon generation kinetics.

The heavy oil yield and natural gas yield evolution models were established through thermal evolution simulation experiments, as shown in Figure 9. The heavy oil yield and natural gas yield evolution models, the heavy oil yield and natural gas yield evolution models are as follows As shown in formula (9) and formula (10), the expressions of formula (9) and formula (10) are as follows:

Heavy oil yield per unit of organic matter＝440.93VR _o ³ -1629VR _o ² +2053.3VR _o -618.7(9)

Unit organic matter natural gas yield = 18.371VR _o ³ +45.684VR _o ² -62.693VR _o +28.05(10)

In the formula, VR _o is the measured maturity parameter vitrinite reflectance.

Establish a model of the measured maturity parameter vitrinite reflectance VR _o with depth, the model is shown in formula (11), and the expression of formula (11) is as follows:

VR _o =0.1605e ^0.535H (11)

In the formula, H is the burial depth of the sample point in m.

4. Calculate the total hydrocarbons generated and discharged at different depth points of shale, as well as the amount of heavy oil, light oil and gas, and evaluate the heterogeneity of oil and gas content of shale.

According to the parameters obtained in the above steps 1 and 2, calculate the unit original hydrocarbon generation potential S _OP , total hydrocarbon generation S _Gen , hydrocarbon expulsion S _Exp and hydrocarbon expulsion coefficient K _P for each shale sample point. The calculation formulas of hydrocarbon generation potential S _OP , total hydrocarbon generation S _Gen , hydrocarbon expulsion S _Exp and hydrocarbon expulsion coefficient K _P are shown in formulas (12), (13), (14), and (15). The formula ( The expressions of 12), (13), (14), and (15) are as follows:

S _OP =TOC ₀ ×D ₀ /0.083(12)

S _Exp = S _OP - (S ₁ +S ₂ )(13)

S _Gen = S _OP - S ₂ (14)

K _P = S _Exp / S _Gen × 100% (15)

In the formula, TOC ₀ is the original organic carbon, D ₀ is the original degradation rate, S ₁ is the free hydrocarbons obtained from the pyrolysis of rocks in the low-temperature stage of Rock-Eval, and S ₂ is the pyrolyzed hydrocarbons obtained in the pyrolysis of rocks in the high-temperature stage of Rock-Eval.

According to the model established in step 3, the oil and gas generation of samples at each depth point are calculated through formula (16) and formula (17). The expressions of formula (16) and formula (17) are as follows:

Production amount of heavy oil per unit sample = yield of heavy oil per unit of organic matter × TOC(16)

Natural gas production per unit sample = □ organic □ natural gas yield × TOC(17)

After obtaining the yield of heavy oil and natural gas, the yield of C ₆ ~C ₁₄ light oil is further obtained. Based on the detected heavy oil and gas, the yield of light oil can be obtained by mutual compensation. According to For the component distribution of the original hydrocarbon generation potential, the light oil yield is obtained by subtracting the pyrolysis hydrocarbon generation yield as shown in formula (18). The expression of formula (18) is as follows:

S _lo = S _Gen - S _ho - S _g (18)

In the formula, S _lo is the light oil yield, S _Gen is the original hydrocarbon generation potential of the sample, S _ho is the heavy oil yield, and S _g is the natural gas yield.

The distribution of heavy oil yield S _ho , light oil yield S _lo , and natural gas yield S _g of each unit sample point is obtained through the above model, and the heterogeneity of oil-bearing and gas-bearing properties of shale is evaluated. Figure 10 shows the distribution of heavy oil yield S _ho , light oil yield S _lo , and natural gas yield S _g for each unit sample point.

According to the obtained above parameters, the evaluation parameter profile of shale hydrocarbon generation is established, and the profile distribution heterogeneity of shale oil and gas resources is evaluated through the evaluation parameter profile.

The third member of the Paleogene Shahejie Formation provided by the evaluation method in this example in the Dongying N38 well of the Bohai Bay Basin was evaluated when the maturity was not very high.

When the maturity is very high, part of the crude oil will be cracked into gas. The above scheme is also applicable, but one more link is added. According to the yield of crude oil cracked into gas, the amount of crude oil cracked into gas will be calculated. The yield of crude oil cracked into gas can be obtained according to the simulation experiment and the dynamics of crude oil cracked into gas, and the change of the yield of crude oil cracked into gas with the maturity parameter VR _o can be obtained. Fig. 11 is a variation model of the crude oil cracking gas production rate obtained according to the crude oil cracking gas simulation experiment. The specific method has been introduced in the existing literature, and the present invention does not introduce it in detail.

The cases provided in this embodiment are obtained based on a large number of measured samples. When a large number of samples are not available, it can also be calculated based on well logging data, because the well logging data has the characteristics of high resolution, and the key parameter organic carbon content can be calculated according to the well logging data, where the organic carbon content is the residual organic carbon content, there are many specific methods, for example, the popular Δlog method is adopted, which is not described in detail in the present invention.

There is a good correlation between residual organic carbon TOC _Rem and pyrolysis parameters S ₂ and S ₁ , because the three can reflect the hydrocarbon generation potential of source rocks. The correlation between TOC _Rem and S ₂ and S ₁ +S ₂ and the relationship between Tmax and depth can be established based on limited measured samples. TOC _Rem and S ₂ and S ₁ + S ₂ are sometimes correlated with segments, and the effect is better.

In this example, Figure 12 shows that the Paleogene measured S ₂ and TOC _Rem segmental correlation distribution in the Dongying sag:

When TOC _Rem <2, S ₂ =2.2441TOC _Rem ² -1.0291TOC _Rem +0.2697 (R ² =0.8947);

When 2≤TOC _Rem <5, S ₂ =7.2813 TOC _Rem -6.3066 (R ² =0.9348);

When 5≦TOC _Rem , S ₂ =3.9918 TOC _Rem +10.424 (R ² =0.9809).

In this example, Figure 13 shows that the Paleogene measured S ₁ +S ₂ and TOC _Rem segmental correlation distribution in Dongying sag:

When TOC _Rem <2, S ₁ +S ₂ =2.8353TOC _Rem ² -1.6797TOC _Rem +0.4725(R ² =0.8547)

When 2≤TOC _Rem <5, S ₁ +S ₂ =7.6804TOC _Rem -6.4302 (R ² =0.8274)

When 5≤TOC _Rem , S ₁ +S ₂ =4.1906TOC _Rem +13.515 (R ² =0.9602)

In this way, the corresponding S ₂ , S ₁ and Tmax values can be further calculated according to the TOC _Rem value predicted by the logging data and the correlation model. Its subsequent calculation is the same as the introduction of the method of the present invention.

The above-mentioned embodiments are used to explain the present invention, rather than to limit the present invention. Within the spirit of the present invention and the protection scope of the claims, any modification and change made to the present invention will fall into the protection scope of the present invention.

Claims (8)

1. nonuniformity evaluates a method for mud shale oil generation tolerance, it is characterized in that: containing following steps:

One, to different depth point intensive sampling on mud shale section, and detect acquisition basic parameter value by Rock-Eval pyrolysis, determine organic matter type: depth direction is sampled every 1-10m sample spot on mud shale section, Rock-Eval pyrolysis analysis is carried out to the sample gathered, and obtains the parameter value of basic parameter by Rock-Eval pyrolysis; Hydrogen index (HI) HI, productive rate indices P I and the hydrocarbon index [100 × S of each depth samples point is determined according to basic parameter ₁]/TOC, S ₁for the free hydrocarbon that the pyrolysis of rock Rock-Eval cold stage obtains, TOC is the actual organic carbon detected, by hydrogen index (HI) HI and underlying parameter determination organic matter type;

Two, conceputal modeling calculate multi-form organic carbon content: according to composition and the transforming principle of organic carbon, organic carbon in mud shale is divided into the conceptual model of different organic carbon form, organic carbon is defined as residual organic carbon, residual effective carbon, residual invalid carbon, discharges organic carbon, discharge effective carbon, original organic carbon, original effective carbon, original invalid carbon, original Organic Carbon TOC total in mud shale ₀comprise discharge Organic Carbon TOC _expwith residual Organic Carbon TOC _rem, then there is relational expression as shown in formula (1), at original Organic Carbon TOC in two parts ₀in, the organic carbon part of converting one-tenth hydro carbons is defined as effective carbon TOC _rea, original Organic Carbon TOC ₀in contained effective carbon and residual Organic Carbon TOC _remin effective carbon be defined as TOC respectively _0-reaand TOC _rem-rea; Raw hydrocarbon potentiality residual in mud shale are transformed by the effective carbon in residual organic carbon, it and residual Organic Carbon TOC _remresidue degrading rate D _remthe relational expression existed is as shown in formula (2); The expression formula of described formula (1) and formula (2) is as follows:

TOC ₀＝TOC _Rem+TOC _Exp(1)

D _Rem＝TOC _Rem-rea/TOC _Rem(2)

Be considered as the transformation ratio that carbon is converted into hydro carbons by 0.083 in current petroleum industry, then there is relational expression as shown in formula (3), the expression formula of formula (3) is as follows:

TOC _Rem-rea＝(S ₁+S ₂)×0.083(3)

In formula, S ₂for the pyrolysed hydrocarbon that the pyrolysis of rock Rock-Eval hot stage obtains,

Then residue degrading rate D _remcalculated by formula (4) and obtain, the expression formula of formula (4) is as follows:

D _Rem＝(S ₁+S ₂)×0.083/TOC _Rem(4)

According to residue degrading rate D _remwith pyrolysis peak temperature T _maxthe figure that crosses determine different organic original degradation rate D ₀;

Organic matter evolution with become in hydrocarbon process, invalid carbon wherein can be considered and remains unchanged, and therefore, there is relational expression as shown in formula (5), the expression formula of formula (5) is as follows:

TOC ₀(1–D ₀)＝TOC _Rem(1–D _Rem)(5)

In described formula (5), TOC ₀(1 – D ₀) represent invalid carbon in primary organic material, be defined as TOC _ine, TOC _rem(1 – D _rem) represent invalid carbon in residual organic matter, be defined as TOC _rem-Ine;

Can be converted into formula (6) and formula (7) by formula (5), the expression formula of formula (6) and formula (7) is as follows:

(1–D _Rem)/(1–D ₀)＝TOC ₀/TOC _Rem(6)

R _C＝TOC ₀/TOC _Rem(7)

In described formula (7), R _cfor the residual organic carbon that records now is to the coefficient of restitution of original organic carbon, be constant factor, without unit;

Meanwhile, also there is relational expression as shown in formula (8), the expression formula of formula (8) is as follows:

TOC ₀–TOC _0-rea＝TOC _Rem–TOC _Rem-rea(8)

In described formula (8), TOC ₀– TOC _0-rearepresent the invalid carbon in primary organic material, be defined as TOC _0-Ine, TOC _rem– TOC _rem-rearepresent the invalid carbon in residual organic matter, be defined as TOC _rem-Ine;

The residue degrading rate D of each sample spot is gone out by above formulae discovery _rem, original organic carbon recovering coefficient R _cand the organic carbon content of often kind of form distributes in the nonuniformity of section, for mud shale oil and gas resource evaluation provides basic data;

Three, design simulation experiment, set up heavy-hydrocarbon oil productive rate and gas yield evolutionary model: choose mud shale sample and do thermal Modeling experiment, obtain Auditory steady-state responses curve, set up mink cell focus productive rate and gas yield evolutionary model, set up actual measurement maturity indices vitrinite reflectance VR _owith change in depth model;

Four, total hydrocarbon amount and heavy oil mass, lightweight oil mass and the amount of coalbed methane generated of mud shale different depth dot generation and discharge is calculated, evaluate the nonuniformity of mud shale oiliness and gas-bearing property: according to the parameters obtained in step one and step 2, calculate each mud shale sample spot unit always raw hydrocarbon amount S _gen, Hydrocarbon yield S _exp; Calculate oil, the gas growing amount of each depth point sample according to the model set up in step 3, on acquisition mink cell focus, gas yield basis, obtain C further ₆~ C ₁₄lightweight oil productive rate; And then obtain the mink cell focus productive rate S of each unit sample point _ho, lightweight oil productive rate S _lo, gas yield S _gdistribution, with the nonuniformity of mink cell focus, lightweight oil and gas-bearing property in quantitative evaluation mud shale; Set up the evaluating sectional view of the raw hydrocarbon of mud shale by the above-mentioned parameter obtained, evaluate mud shale hydrocarbon resources Soil profile nonuniformity by evaluating sectional view.

2. nonuniformity according to claim 1 evaluates the method for mud shale oil generation tolerance, and it is characterized in that: in step one, described basic parameter comprises the residual Organic Carbon TOC of actual measurement _rem, the pyrolysis of rock Rock-Eval cold stage obtain free hydrocarbon S ₁, the pyrolysis of rock Rock-Eval hot stage obtain pyrolysed hydrocarbon S ₂with pyrolysis peak temperature T _max, wherein, pyrolysis peak temperature T _maxfor the pyrolysed hydrocarbon S that the pyrolysis of rock Rock-Eval hot stage obtains ₂corresponding peak value, the residual Organic Carbon TOC of actual measurement _remfor now by the actual Organic Carbon TOC detected of sample; Described hydrogen index (HI) HI represents the raw hydrocarbon potentiality of mud shale, and productive rate indices P I represents degree of ripeness and the thermal evolution of mud shale, by hydrogen index (HI) HI and pyrolysis peak temperature T _maxcross figure determination organic matter type.

3. nonuniformity according to claim 1 evaluates the method for mud shale oil generation tolerance, it is characterized in that: in described step 3, chooses representative bulk homogeneous mudstone sample, be divided into 9 parts and put into respectively in heating kettle, does thermal Modeling experiment; 9 increment product are by the speed of 50 DEG C/h, respectively from experimental temperature by room temperature to 250 DEG C, 300 DEG C, 350 DEG C, 400 DEG C, 450 DEG C, 500 DEG C, 550 DEG C, 600 DEG C, 650 DEG C of 9 terminal temperatures, when every increment product arrive the terminal temperature of oneself, distilled water is injected with the speed of 2ml/min with constant speed constant flow pump, take oil and the gaseous product of discharge in time out of, the oil obtain every increment product thermal simulation experiment and gaseous product are collected and are measured.

4. nonuniformity according to claim 1 evaluates the method for mud shale oil generation tolerance, it is characterized in that: in step 3, described mink cell focus productive rate and gas yield evolutionary model are as shown in formula (9) and formula (10), and the expression formula of formula (9) and formula (10) is as follows:

The organic mink cell focus productive rate=440.93VR of unit _o ³-1629VR _o ²+ 2053.3VR _o-618.7 (9)

Organic gas yield=the 18.371VR of unit _o ³+ 45.684VR _o ²-62.693VR _o+ 28.05 (10)

In formula, VR _ofor actual measurement maturity indices vitrinite reflectance.

5. nonuniformity according to claim 1 evaluates the method for mud shale oil generation tolerance, it is characterized in that: in step 3, described actual measurement maturity indices vitrinite reflectance VR _owith change in depth model as shown in formula (11), the expression formula of formula (11) is as follows:

VR _o＝0.1605e ^0.535H(11)

In formula, H is the depth of burial of sample spot, and unit is: m.

6. nonuniformity according to claim 1 evaluates the method for mud shale oil generation tolerance, it is characterized in that: in step 4, also calculates original hydrocarbon potential S according to the parameters obtained in step one and step 2 _oPand hydrocarbon expulsive coefficient K _p, described original hydrocarbon potential S _oP, total raw hydrocarbon amount S _gen, Hydrocarbon yield S _expand hydrocarbon expulsive coefficient K _pcomputing formula as shown in formula (12), (13), (14), (15), the expression formula of formula (12), (13), (14), (15) is as follows:

S _OP＝TOC ₀×D ₀/0.083(12)

S _Exp＝S _OP－(S ₁+S ₂)(13)

S _Gen＝S _OP－S ₂(14)

K _P＝S _Exp/S _Gen×100％(15)

。

7. nonuniformity according to claim 1 evaluates the method for mud shale oil generation tolerance, it is characterized in that: in step 4, calculated oil, the gas growing amount of each depth point sample by formula (16) and formula (17), the expression formula of formula (16) and formula (17) is as follows:

Organic mink cell focus productive rate × TOC (16) of unit sample mink cell focus growing amount=unit

Organic gas yield × the TOC (17) of unit sample rock gas growing amount=unit

。

8. nonuniformity according to claim 1 evaluates the method for mud shale oil generation tolerance, it is characterized in that: in step 4, component according to original hydrocarbon potential is distributed, adopt the minusing of the cracking hydrocarbon productive rate as shown in formula (18) to obtain lightweight oil productive rate, the expression formula of formula (18) is as follows:

S _lo＝S _Gen－S _ho－S _g(18)

In formula, S _lofor lightweight oil productive rate, S _genfor the original hydrocarbon potential of sample, S _hofor mink cell focus productive rate, S _gfor gas yield.