CN112052429A - Dessert region prediction method and device for compact oil source rock of salinization lake basin - Google Patents

Dessert region prediction method and device for compact oil source rock of salinization lake basin Download PDF

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CN112052429A
CN112052429A CN202010672599.9A CN202010672599A CN112052429A CN 112052429 A CN112052429 A CN 112052429A CN 202010672599 A CN202010672599 A CN 202010672599A CN 112052429 A CN112052429 A CN 112052429A
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胡素云
白斌
李永新
陶士振
陈燕燕
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Petrochina Co Ltd
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Abstract

The invention provides a dessert area prediction method and device for a compact oil source rock of a salinization lake basin, wherein the method comprises the following steps: collecting a sample of the compact oil source rock of the salinization lake basin and determining a plurality of evaluation parameters of the sample; determining the hydrocarbon discharge characteristics corresponding to the sample of the compact oil source rock of the salinization lake basin; performing cluster analysis based on the hydrocarbon expulsion features and a plurality of evaluation parameters to determine target parameters of the sample; determining a quantitative index corresponding to the target parameter according to a trend line between the target parameter and the hydrocarbon discharge characteristic; and determining the dessert area of the compact oil source rock of the salinized lake basin according to the quantitative index. The method can predict the dessert region of the salted compact oil, and improve the accuracy of determination prediction, so that the determination prediction of the continental-facies salted lake basin compact oil dessert has accuracy and scientificity.

Description

Dessert region prediction method and device for compact oil source rock of salinization lake basin
Technical Field
The invention relates to the technical field of oil exploration, in particular to a dessert region prediction method and device for a compact oil source rock of a salinized lake basin.
Background
Continental compact oil has become an important exploration and development field, and a quantitative evaluation method for the effectiveness of hydrocarbon source rocks becomes an important research content for the evaluation of compact oil and gas desserts and resource evaluation. The quality of the source rock is different and changed along with different sedimentary facies zones, for example, the abundance change range of organic matter can be from 0.2% to 28%, especially the source rock in the salinization lake basin contains or coexists with carbonate, sulfate or chloride and other evaporite to different degrees, the heterogeneous degree is strong, the processes of generating and discharging hydrocarbon by organic matter are different from those of the fresh water lake basin, and the salinity has obvious control effect on the hydrocarbon discharge of the source rock in the salinization lake basin. From the perspective of hydrocarbon generation potential of the source rock, the abundance of organic matters of the source rock is judged by using parameters such as total organic carbon, chloroform bitumen, hydrocarbon generation potential, total hydrocarbon and the like, and the method is a common method for evaluating the effectiveness of the source rock of the fresh water lake basin.
At present, the research of the source rocks of the salinization lake basin mainly focuses on the aspects of whether the high-quality source rocks develop, the development mechanism and the main control factors of the source rocks, the hydrocarbon generation characteristics of the source rocks and the like. Sweet spot prediction for a source rock of a salinized lake basin is also by means of petrophysical techniques for features such as reservoir fractures, brittleness, etc. The petrophysical technique cannot accurately predict the dessert region of the continental compact oil special geology.
Therefore, a method for predicting a sweet spot aiming at the special geological condition of the continental phase compact oil is needed.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a dessert area prediction method and device for salinization of lake basin compact oil source rock, which specifically comprise the following technical scheme:
in a first aspect, the invention provides a method for predicting a sweet spot of a salty lake basin compact oil source rock, which comprises the following steps:
collecting a sample of the compact oil source rock of the salinization lake basin and determining a plurality of evaluation parameters of the sample;
determining the hydrocarbon discharge characteristics corresponding to the sample of the compact oil source rock of the salinization lake basin;
performing cluster analysis based on the hydrocarbon expulsion features and a plurality of evaluation parameters to determine target parameters of the sample;
determining a quantitative index corresponding to the target parameter according to a trend line between the target parameter and the hydrocarbon discharge characteristic;
and determining the dessert area of the compact oil source rock of the salinized lake basin according to the quantitative index.
Wherein, after the sample of the compact oil source rock of the salinization lake basin is collected, the method further comprises the following steps:
determining the equivalent boron content of the sample, and classifying the sample according to the equivalent boron content;
and determining the salinity corresponding to each classification.
Wherein the plurality of evaluation parameters includes: salinity, organic carbon content, soluble hydrocarbon content, pyrolytic hydrocarbon content, peak top temperature, organic matter abundance, mineral content and source rock thermal evolution maturity.
Wherein the determining of the hydrocarbon discharge characteristics corresponding to the sample of the compact oil source rock of the salinization lake basin comprises the following steps:
performing organic carbon determination on the sample of the compact oil source rock of the salinization lake basin to obtain the content of organic carbon;
calculating hydrocarbon generation characteristics and hydrocarbon stagnation characteristics corresponding to the samples of the compact oil source rocks of the salinization lake basin according to the content of the organic carbon;
determining the hydrocarbon expulsion characteristics based on the hydrocarbon production characteristics and the stagnant hydrocarbon characteristics.
Wherein the hydrocarbon discharge characteristic is the hydrocarbon discharge efficiency of the compact oil source rock of the salinization lake basin.
Wherein the performing cluster analysis based on the hydrocarbon discharge characteristics and a plurality of evaluation parameters to determine target parameters of the sample comprises:
clustering a plurality of evaluation parameters by using the hydrocarbon discharge efficiency of the compact oil source rock of the salinization lake basin as a clustering center by adopting a k-means clustering algorithm to obtain a clustering parameter classification set;
and determining the evaluation parameters in the clustering parameter classification set as target parameters.
Determining a quantitative index corresponding to the target parameter according to a trend line between the target parameter and the hydrocarbon discharge characteristic comprises the following steps:
determining a target value corresponding to the hydrocarbon discharge characteristic;
determining a quantitative value of the target parameter corresponding to a target value corresponding to the hydrocarbon discharge characteristic on the trend line;
and determining the quantitative value of the target parameter as the quantitative index.
In a second aspect, the present invention provides a device for predicting a sweet spot of a salty lake basin compact oil source rock, comprising:
the system comprises a collecting unit, a processing unit and a processing unit, wherein the collecting unit is used for collecting a sample of the compact oil source rock of the salinization lake basin and determining a plurality of evaluation parameters of the sample;
the characteristic unit is used for determining the hydrocarbon discharge characteristics corresponding to the sample of the compact oil source rock of the salinization lake basin;
a target parameter unit for performing cluster analysis based on the hydrocarbon discharge characteristics and a plurality of evaluation parameters to determine a target parameter of the sample;
the quantitative unit is used for determining a quantitative index corresponding to the target parameter according to a trend line between the target parameter and the hydrocarbon discharge characteristic;
and the prediction unit is used for determining the sweet spot of the compact oil source rock of the salinized lake basin according to the quantitative index.
Wherein, still include:
the classification unit is used for determining the equivalent boron content of the sample and classifying the sample according to the equivalent boron content;
and the salinity unit is used for determining the salinity corresponding to each classification.
Wherein the feature unit includes:
the measuring subunit is used for carrying out organic carbon measurement on the sample of the compact oil source rock of the salinization lake basin to obtain the content of organic carbon;
the calculation unit is used for calculating the hydrocarbon generation characteristics and the hydrocarbon stagnation characteristics corresponding to the samples of the compact oil source rocks of the salinization lake basin according to the content of the organic carbon;
a characteristic subunit for determining the hydrocarbon expulsion characteristic based on the hydrocarbon production characteristic and the hydrocarbon stagnation characteristic.
Wherein the hydrocarbon discharge characteristic is the hydrocarbon discharge efficiency of the compact oil source rock of the salinization lake basin.
Wherein the target parameter unit includes:
the clustering subunit is used for clustering a plurality of evaluation parameters by using the hydrocarbon discharge efficiency of the compact oil source rock of the salinization lake basin as a clustering center and adopting a k-means clustering algorithm to obtain a clustering parameter classification set;
and the target parameter subunit is used for determining the evaluation parameters in the clustering parameter classification set as target parameters.
Wherein the quantifying unit comprises:
a target value subunit, configured to determine a target value corresponding to the hydrocarbon discharge characteristic;
a quantitative value subunit, configured to determine, on the trend line, a quantitative value of the target parameter corresponding to the target value corresponding to the hydrocarbon discharge characteristic;
and the quantitative subunit is used for determining the quantitative value of the target parameter as the quantitative index.
In a third aspect, the present invention provides an electronic device, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method for predicting the sweet spot region of the salty lake basin compact oil source rock when executing the program.
In a fourth aspect, the present invention provides a computer readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the method for predicting a sweet spot of a salty lake basin compact oil source rock.
According to the technical scheme, the dessert region prediction method and device for the salty lake basin compact oil source rock are characterized in that samples of the salty lake basin compact oil source rock are collected, and a plurality of evaluation parameters of the samples are determined; determining the hydrocarbon discharge characteristics corresponding to the sample of the compact oil source rock of the salinization lake basin; performing cluster analysis based on the hydrocarbon expulsion features and a plurality of evaluation parameters to determine target parameters of the sample; determining a quantitative index corresponding to the target parameter according to a trend line between the target parameter and the hydrocarbon discharge characteristic; the dessert area of the salty lake basin compact oil source rock is determined according to the quantitative index, the dessert area of the salty compact oil can be predicted, the accuracy of determination prediction is improved, and the accuracy and the scientificity of determination prediction of the continental facies salty lake basin compact oil dessert are achieved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a first flow chart of a method for predicting a sweet spot of a salty lake basin compact oil source rock according to an embodiment of the invention.
Fig. 2 is a second flow chart of the dessert region prediction method for salinization of lake basin compact oil source rock in the embodiment of the invention.
FIG. 3 is a schematic view of the entire flow of the dessert region prediction method for the salty lake basin compact oil source rock in the embodiment of the present invention.
FIG. 4 is a geological profile of a source rock of compact oil of a salinized lake basin in the method for predicting a sweet spot region of the source rock of compact oil of a salinized lake basin in an embodiment of the invention.
FIG. 5 is a graph showing the relationship between salinity and hydrocarbon discharge of the saline lake basin compact oil source rock in the dessert region prediction method for the saline lake basin compact oil source rock in the embodiment of the present invention.
FIG. 6 is a TOC-hydrocarbon discharge relationship diagram of the salty lake basin compact oil source rock in the method for predicting the sweet spot region of the salty lake basin compact oil source rock according to the embodiment of the invention.
Fig. 7 is a schematic structural diagram of a dessert region predicting device for salinization of lake basin compact oil source rock in the embodiment of the invention.
Fig. 8 is a schematic structural diagram of an electronic device in an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides an embodiment of a dessert region prediction method for a salinized lake basin compact oil source rock, and referring to fig. 1, the dessert region prediction method for the salinized lake basin compact oil source rock specifically comprises the following contents:
s101: collecting a sample of the compact oil source rock of the salinization lake basin and determining a plurality of evaluation parameters of the sample;
in the step, according to the distribution of the dense oil source rocks of the salinization lake basin, series source rock samples with different salinity are collected according to different positions of the lake basin. For example: deep lake facies, semi-deep lake facies, and shore shallow lake facies.
The evaluation parameters in this step are parameters that are considered to have an influence on the hydrocarbon generation and hydrocarbon discharge of the sample of the salty lake basin compact oil source rock. When the evaluation parameters are determined, the evaluation parameters can be set according to the requirements.
In this embodiment, the plurality of evaluation parameters at least include: salinity, organic carbon content, soluble hydrocarbon content, pyrolytic hydrocarbon content, peak top temperature, organic matter abundance, mineral content and source rock thermal evolution maturity.
S102: determining the hydrocarbon discharge characteristics corresponding to the sample of the compact oil source rock of the salinization lake basin;
the hydrocarbon discharge characteristic bar corresponding to the sample of the compact oil source rock of the salinization lake basin is the hydrocarbon discharge amount, the hydrocarbon generation amount or the hydrocarbon discharge efficiency of the compact oil source rock of the salinization lake basin.
In the present example, the hydrocarbon discharge is characterized by the hydrocarbon discharge efficiency.
S103: performing cluster analysis based on the hydrocarbon expulsion features and a plurality of evaluation parameters to determine target parameters of the sample;
the influence factors of effective hydrocarbon discharge from the source rocks in the lakes and the basins are many, including not only the difference in quality of the source rocks but also various factors such as lithology, physical properties, and contact relationship with the source rocks. The salinity, mineral characteristics and structure of the source rock of the salinized lake basin have obvious control effect on hydrocarbon discharge.
In the step, the hydrocarbon discharge efficiency of the compact oil source rock of the salinization lake basin is taken as a clustering center, wherein the hydrocarbon discharge efficiency is taken as the clustering center to judge the evaluation parameter which has a large influence on the hydrocarbon discharge efficiency in the plurality of evaluation parameters. Clustering the evaluation parameters by adopting a k-means clustering algorithm to obtain a clustering parameter classification set; and determining that the evaluation parameters in the clustering parameter classification set have great influence on the hydrocarbon discharge efficiency. In specific implementation, the evaluation parameters in the clustering parameter classification set are determined as target parameters.
S104: and determining a quantitative index corresponding to the target parameter according to the trend line between the target parameter and the hydrocarbon discharge characteristic.
In this step, a trend line between each target parameter and the sample hydrocarbon discharge characteristic can be determined according to the determined target parameter, that is, the influence of a single target parameter on the hydrocarbon discharge efficiency is determined, and specifically, a single variable can be controlled to determine the trend line between each target parameter and the sample hydrocarbon discharge characteristic. In practice, a target parameter is too low to determine the hydrocarbon expulsion capability of the sample. It is desirable to determine the effective lower limit of the target parameter in the trend line of the hydrocarbon expulsion characteristics.
Determining a target value corresponding to the hydrocarbon discharge characteristic when determining the effective lower limit of the target parameter; the target value for the hydrocarbon expulsion characteristic is the minimum value of the hydrocarbon expulsion efficiency under the influence of a target parameter. And determining the quantitative value of the target parameter corresponding to the target value corresponding to the hydrocarbon discharge characteristic on the trend line, namely determining the quantitative value of the target parameter corresponding to the minimum value of the hydrocarbon discharge efficiency, and determining the quantitative value of the target parameter as a quantitative index.
S105: and determining the dessert area of the compact oil source rock of the salinized lake basin according to the quantitative index.
In this step, the quantitative indexes corresponding to the target parameters are determined, and the region satisfying the quantitative indexes corresponding to all the target parameters is determined to be the sweet spot region.
As can be seen from the above description, according to the dessert region prediction method and device for the salty lake basin compact oil source rock provided by the embodiment of the present invention, a sample of the salty lake basin compact oil source rock is collected, and a plurality of evaluation parameters of the sample are determined; determining the hydrocarbon discharge characteristics corresponding to the sample of the compact oil source rock of the salinization lake basin; performing cluster analysis based on the hydrocarbon expulsion features and a plurality of evaluation parameters to determine target parameters of the sample; determining a quantitative index corresponding to the target parameter according to a trend line between the target parameter and the hydrocarbon discharge characteristic; determining a dessert area of the compact oil source rock of the salinization lake basin according to the quantitative index; the method can predict the dessert region of the salted compact oil, improves the accuracy of determination prediction, and enables the determination prediction of the desert region of the salted lake basin compact oil to be accurate and scientific.
In an embodiment of the present invention, referring to fig. 2, the method for predicting the sweet spot of the salty lake basin compact oil source rock further includes step S106 and step S107 after step S101, and includes the following steps:
s106: determining the equivalent boron content of the sample, and classifying the sample according to the equivalent boron content;
s107: and determining the salinity corresponding to each classification.
In the embodiment, a system environment analysis test is carried out on the collected hydrocarbon source rock sample; and (3) testing the principal component, trace element and rare earth element by using an inductively coupled plasma spectrometer (ICP), recovering the deposition environment of the source rock of the salinization lake basin by using the system, calculating equivalent boron content by using the boron element and clay mineral content, and quantitatively determining salinity values of different source rocks. Among them, the equivalent boron content: b is*＝8.5×BSample (I)/K2OSample (I)，BSample (I)Is the boron content of the sample, K2OSample (I)Is sample K2And (4) the content of O. The source rock is divided into fresh water and low salinity according to salinity difference (equivalent to boron less than 200 multiplied by 10)-6) Medium salinity brackish water deposition environmental source rock (equivalent to boron 200X 10)-6-300×10-6) With high salinity source rock (equivalent to boron 300X 10)-6-400×10-6) And three types, namely, the samples are divided into three types according to the equivalent boron content. By executing steps S101 to S105 in the above embodiment, the evaluation index corresponding to each of the three categories can be determined.
In the above embodiment, the plurality of evaluation parameters are obtained by performing organic carbon content measurement, rock pyrolysis analysis, and vitrinite reflectance measurement on the sample.
For example: and (3) carrying out organic carbon content determination on the collected hydrocarbon source rock sample: grinding the sample to a particle size of less than 0.2mm by using a carbon-sulfur tester or a carbon tester, and weighing 0.01g-1.00g of sample according to the type of the sample. Slowly adding excessive hydrochloric acid solution into a container containing the sample, placing the container on a water bath pot or an electric hot plate, controlling the temperature at 60-80 ℃, and dissolving the sample for more than 2 hours until the reaction is complete. The acid treated sample was placed in a porcelain crucible on a suction filter and washed with distilled water to neutrality. And (3) putting the porcelain crucible containing the sample into a drying oven at the temperature of 60-80 ℃ and drying for later use. Adding 1g of scrap iron fluxing agent and 1g of tungsten particle fluxing agent into a dried porcelain crucible containing a sample, inputting the mass of the sample through a human-computer interaction interface, and measuring on a computer to obtain a content numerical value, namely the total organic carbon content TOC;
performing rock pyrolysis analysis on the collected hydrocarbon source rock sample: placing a proper amount of hydrocarbon source rock sample in a pyrolysis furnace, adopting a rock fast pyrolysis technology to analyze, firstly heating to 300 ℃, keeping the temperature for 3 minutes, measuring a free soluble hydrocarbon peak P1, and calculating the soluble hydrocarbon content S according to the peak area1(ii) a Then, heating was continued to 600 ℃ at a rate of 50 ℃/min, and the pyrolytic hydrocarbon peak P was measured2The content S of the pyrolysis hydrocarbon is calculated from the peak area2And peak top temperature Tmax；
And performing vitrinite reflectivity test on the hydrocarbon source rock samples with similar depths in the basin to determine the thermal evolution maturity characteristics of the hydrocarbon source rock.
Furthermore, the system lithofacies and microstructure analysis test can be carried out on the collected hydrocarbon source rock sample; by using test methods such as XRD, rock slices, SEM and CT, lithology, mineral content and pore development characteristics of the source rock are systematically observed, and the microstructure and lithofacies characteristics of the source rock of the salinization lake basin are determined;
in the above embodiment, determining the hydrocarbon discharge characteristics corresponding to the sample of the compact oil source rock of the salinized lake basin includes:
organic carbon determination is carried out on the sample of the compact oil source rock of the salinization lake basin to obtain the TOC (total organic carbon)Nowadays(ii) a To the content TOC of the organic carbonNowadaysCorrecting to obtain the corrected TOC of the original TOCOriginal；
Original TOC correction: TOCOriginal＝TOCNowadays×(1200–HINowadays)/(1200–HIOriginal)；
Wherein, HINowadaysIs the hydrogen index, HI, of a present-day green sampleOriginalHydrogen index of the original green sample.
Calculating hydrocarbon generation characteristics and hydrocarbon stagnation characteristics corresponding to the samples of the compact oil source rocks of the salinization lake basin according to the content of the organic carbon; wherein the hydrocarbon generation characteristic is hydrocarbon amount, and the hydrocarbon stagnation characteristic is hydrocarbon stagnation amount, and the specific calculation is as follows:
calculation of amount of Hydrocarbon CHydrocarbon generation：CHydrocarbon generation＝CLow degree of ripeness–COriginal；
Calculation of amount of hydrocarbons discharged CHydrocarbon discharge：CHydrocarbon discharge＝CHydrocarbon generation–CStagnant hydrocarbons；；
Wherein, CLow degree of ripenessFor immature primary Hydrocarbon potential, COriginalNormalizing the residual hydrocarbon potential of the sample to an initial green state; cStagnant hydrocarbonsIs the retained hydrocarbon content of the sample;
determining an expulsion characteristic based on the hydrocarbon-producing characteristic and the stagnant hydrocarbon characteristic, wherein the expulsion characteristic is an expulsion efficiency E.
Hydrocarbon removal efficiency E: e ═ CHydrocarbon discharge/CHydrocarbon generationX 100. The description shows that the hydrocarbon discharge amount of the hydrocarbon source rocks of the continental facies salinization lake basin is calculated quantitatively based on the special geological features of the hydrocarbon source rocks of the salinization lake basin, the effective lower limit of the compact oil source rocks of the salinization lake basin is further evaluated quantitatively, the influence of the hydrocarbon discharge effect on the effective judgment of the hydrocarbon source rocks is fully considered, and the environment sources with different salinity of the salinization lake basin are establishedThe correlation between the rock and the hydrocarbon discharge efficiency realizes the quantitative evaluation of the effectiveness of the continental facies saltwater lake basin hydrocarbon source rock, and provides evaluation basis for the exploration prospect of the continental facies saltwater lake basin compact oil.
To further illustrate the present solution, the present invention provides a full-flow embodiment of a method for predicting a sweet spot region of a salty lake basin compact oil source rock, and referring to fig. 3, the method for predicting a sweet spot region of a salty lake basin compact oil source rock specifically includes the following contents:
collecting hydrocarbon source rock samples of different salinity series including deep lake phase, semi-deep lake phase and shoreside lake phase according to the distribution characteristics of the land-based salty lake basin compact oil hydrocarbon source rock and according to different positions of the lake basin;
carrying out system environment analysis and test on the collected hydrocarbon source rock sample; and (3) testing the principal component, trace element and rare earth element by using an inductively coupled plasma spectrometer (ICP), recovering the deposition environment of the source rock of the salinization lake basin by using the system, calculating equivalent boron content by using the boron element and clay mineral content, and quantitatively determining salinity values of different source rocks. Among them, the equivalent boron content: b is*＝8.5×BSample (I)/K2OSample (I)，BSample (I)Is the boron content of the sample, K2OSample (I)Is sample K2And (4) the content of O. The source rock is divided into fresh water and low salinity according to salinity difference (equivalent to boron less than 200 multiplied by 10)-6) Medium salinity brackish water deposition environmental source rock (equivalent to boron 200X 10)-6-300×10-6) With high salinity source rock (equivalent to boron 300X 10)-6-400×10-6) Three types are selected; and carrying out systematic analysis and test on the collected source rock samples with different salinity in a classified manner.
And (3) carrying out organic carbon content determination on the collected hydrocarbon source rock sample: grinding the sample to a particle size of less than 0.2mm by using a carbon-sulfur tester or a carbon tester, and weighing 0.01g-1.00g of sample according to the type of the sample. Slowly adding excessive hydrochloric acid solution into a container containing the sample, placing the container on a water bath pot or an electric hot plate, controlling the temperature at 60-80 ℃, and dissolving the sample for more than 2 hours until the reaction is complete. The acid treated sample was placed in a porcelain crucible on a suction filter and washed with distilled water to neutrality. And (3) putting the porcelain crucible containing the sample into a drying oven at the temperature of 60-80 ℃ and drying for later use. Adding 1g of scrap iron fluxing agent and 1g of tungsten particle fluxing agent into a dried porcelain crucible containing a sample, inputting the mass of the sample through a human-computer interaction interface, and measuring on a computer to obtain a content numerical value, namely the total organic carbon content TOC;
performing rock pyrolysis analysis on the collected hydrocarbon source rock sample: placing a proper amount of hydrocarbon source rock sample in a pyrolysis furnace, adopting a rock fast pyrolysis technology to analyze, firstly heating to 300 ℃, keeping the temperature for 3 minutes, measuring a free soluble hydrocarbon peak P1, and calculating the soluble hydrocarbon content S according to the peak area1(ii) a Then, heating was continued to 600 ℃ at a rate of 50 ℃/min, and the pyrolytic hydrocarbon peak P was measured2The content S of the pyrolysis hydrocarbon is calculated from the peak area2And peak top temperature Tmax；
Performing vitrinite reflectivity test on the hydrocarbon source rock samples with similar depths in the basin to determine the characteristics of the thermal evolution maturity of the hydrocarbon source rock;
carrying out system lithofacies and microstructure analysis and test on the collected hydrocarbon source rock sample; by using test methods such as XRD, rock slices, SEM and CT, lithology, mineral content and pore development characteristics of the source rock are systematically observed, and the microstructure and lithofacies characteristics of the source rock of the salinization lake basin are determined;
testing the low-maturity (Ro < 0.6%) hydrocarbon source rock geological analysis of the salinization area to be tested, and calculating the hydrocarbon discharge characteristics of the collected hydrocarbon source rock sample by using a formula 1 according to a substance balance principle;
correction of raw TOC-TOCOriginal＝TOCNowadays×(1200–HINowadays)/(1200–HIOriginal)；
Calculating the amount of hydrocarbon CHydrocarbon generation＝CLow degree of ripeness–COriginal；
Calculating the amount of hydrocarbons discharged CHydrocarbon discharge＝CHydrocarbon generation–CStagnant hydrocarbons；
Obtaining the hydrocarbon discharging efficiency of E ═ CHydrocarbon discharge/CHydrocarbon generation×100；
The influence factors of effective hydrocarbon discharge of the fresh water lake basin hydrocarbon source rock are quite many, and the influence factors include not only the quality difference of the hydrocarbon source rock, but also various factors such as lithology, physical characteristics and contact relation with the hydrocarbon source rock. The salinity, mineral characteristics and structure of the source rock of the salinized lake basin have obvious control effect on hydrocarbon discharge.
Determining evaluation parameters closely related to the hydrocarbon discharge efficiency of the area to be measured by utilizing a cluster analysis method according to the obtained data;
and determining an evaluation parameter and a hydrocarbon discharge capacity trend line according to the obtained evaluation parameter, and quantitatively calculating to obtain an effective hydrocarbon source rock evaluation index.
Specific examples are as follows:
the selected region is a two-fold continental facies salinization lake basin compact oil hydrocarbon source rock which is taken as an anatomical object, the area of the lake basin in the two-fold period of deposition is large, the depth of lake water is large, the stable receiving and continuous deposition time is long, and a mixed rock combination with various frequent interbedded layers such as argillaceous dolomite, cloud mudstone, tufaceous siltstone and the like is formed. Compared with a fresh water lake basin, the mud shale is formed in the salt water lake basin, the gamma-paraffins and daucane in the source rock extract are high, the deposition environment is indicated to be a salt water lake environment, volcanic substances are commonly developed, lithology is complex and changeable, the abundance of organic carbon is 1.1-13.4%, the average abundance is 4.9%, Ro is 0.5-1.3%, the hydrogen index is mainly distributed in 600-doped 800mg/g TOC, S is distributed in the salt water lake basin1The value is from 0.01 to 3mg.g/TOC, S2The value is 0.06-110mg.g/TOC, the ratio of the sapropel group in the organic matter is higher than 70
vol.%, matrix type I-II1The vitrinite reflectivity is 0.6-1.1%, the thickness distribution is 240m, and the vitrinite has geological characteristics of large thickness and good quality.
The research system collects 73 basin hydrocarbon source rock samples, and the system carries out continuous tests on the geological parameters such as organic matter abundance, rock pyrolysis, main trace element test and the like, so that the quantitative evaluation and prediction of the effectiveness of the hydrocarbon source rock are realized.
Firstly, carrying out system environment analysis and test on collected source rock samples, testing main amount, trace amount and rare earth elements, systematically recovering the deposition environment of the source rock in the salinization lake basin, calculating equivalent boron content by using the content of boron elements and clay minerals, and quantitatively determining salinity values of different source rocks. The equivalent boron content of the hydrocarbon source rock of the salinized lake basin in the research area is 183 multiplied by 10-6-2530×10-6Average 519 × 10-6High salinity as is typicalA source rock. According to the distribution characteristics of equivalent boron, the method can be divided into fresh water and low salinity source rock (equivalent boron is less than 200 multiplied by 10)-6) Medium salinity brackish water deposition environmental source rock (equivalent to boron 200X 10)-6-300×10-6) With high salinity source rock (equivalent to boron 300X 10)-6-400×10-6) And (4) three types.
Secondly, calculate:
correction of raw TOC-TOCOriginal＝TOCNowadays×(1200–HINowadays)/(1200–HIOriginal)；
Calculating the amount of hydrocarbon CHydrocarbon generation＝CLow degree of ripeness–COriginal；
Calculating the amount of hydrocarbons discharged CHydrocarbon discharge＝CHydrocarbon generation–CStagnant hydrocarbons；
Obtaining the hydrocarbon discharging efficiency of E ═ CHydrocarbon discharge/CHydrocarbon generation×100；
The hydrocarbon discharge efficiency calculation generally takes the hydrocarbon source rock as a whole, the degree of hydrocarbon discharge of the whole is measured, the calculation result at this time is the hydrocarbon discharge effect on the surrounding rock in the maturation process of each depth section sample, and the hydrocarbon discharge effect in the source of the liquid hydrocarbon of the source rock is reflected more. Referring to fig. 4, the average hydrocarbon-discharging efficiency of the source rock of the salinized lake phase is higher by calculation according to the formula, the average hydrocarbon-discharging efficiency is 62%, and the hydrocarbon-discharging amount is 8.8mg/g rock.
The source rock of the salinized lake basin in the research area has extremely strong heterogeneity. The hydrocarbon-expelling efficiency is negative because the amalgamated cloud rocks, which have high dolomite and calcite contents and low TOC contents, are derived from quartz and feldspar minerals supplied from land sources, do not have a hydrocarbon-expelling effect but store hydrocarbons as a reservoir. The hydrocarbon storage layer is generally distributed in the layer section with higher physical property and higher cloud quality content, and is similar to the conventional reservoir. The intervals with higher hydrocarbon expulsion occurred mainly in the samples with higher TOC and developed streaks.
Secondly, by utilizing the analysis of microstructures, lithology and the like, the hydrocarbon storage layer is generally distributed in the hydrocarbon storage layer with higher physical property and higher sand content, and is similar to the conventional hydrocarbon storage layer. The intervals with higher hydrocarbon expulsion occurred mainly in the samples with higher TOC and developed streaks. The higher the efficiency of discharging the liquid hydrocarbon of the source rock to a near-source reservoir stratum, the more beneficial to the efficient development of shale oil. Research shows that the discharge efficiency of liquid hydrocarbon is controlled by the TOC content of source rock, mineral composition, a striated layer structure and thermal maturity. The higher the TOC of the source rock, the lower the clay mineral content, and the higher the hydrocarbon discharge efficiency. Among them, the more developed the hydrocarbon source rock, the higher the hydrocarbon generation and migration efficiency. The hydrocarbon generation potential of the mud shale developing the horizontal striated layer is often superior to that of massive source rock due to the enrichment of organic matters, compared with a fresh water lake basin, the salinized lake basin has strong hydrocarbon discharge capacity, and the striated layer-shaped organic-rich shale has high hydrocarbon discharge capacity and is a compact oil-bearing oil-producing rock. Meanwhile, the organic texture layer can be used as an effective channel for migration and accumulation of liquid hydrocarbons. Because of their special mineral composition and sedimentary structure, they tend to develop many types of reservoir spaces. In addition, the striae is an important influencing factor influencing the fracturing performance of the shale, and controls the crack propagation rule in the shale fracturing process. Therefore, the hydrocarbon source rock with the developed striation layer is an ideal shale oil exploration field.
Meanwhile, parameters such as organic matter abundance, mineral composition, hydrocarbon discharge efficiency and the like are subjected to cluster analysis by combining a Kmeans algorithm, and salinity, TOC, a striated layer structure and mineral content are screened as evaluation indexes. Among them, as shown in fig. 5, salinity has obvious correlation and stage with the hydrocarbon discharging amount and efficiency of the dense oil source rock of the salinized lake basin (fig. 3). In conclusion, for the compact oil of the middle-high maturity salt water lake basin, the TOC is more than 4 percent of the lamellar tuff/marbled rock, the hydrocarbon discharge efficiency is high, and the compact oil is a sweet spot beneficial area.
Meanwhile, physical simulation experiments of the low-maturity source rocks of the salinization lakes and basins show that the source rocks with high organic matter abundance have high hydrocarbon discharge efficiency and high hydrocarbon stagnation efficiency and are consistent with the results of geochemical analysis. Comprehensively evaluating the effectiveness results of the compact oil hydrocarbon source rock of the salinized lake basin:
1. when the forming environment of the saline lake basin hydrocarbon source rock is in a low salinity stage (equivalent to the boron content of less than 230 multiplied by 10)-6) The higher the salinity, the lower the amount of hydrocarbons removed, the reduction in hydrocarbons removed from 20.31mg/g.rock to about 7.6 mg/g.rock;
2. when the formation environment of the saline lake basin hydrocarbon source rock is in a medium-salinity brackish water deposition environment (equivalent to boron 230 multiplied by 10)-6-500×10-6) The higher the salinity, the higher the hydrocarbon output, which drops from 7.58mg/g.rock to about 15.32 mg/g.rock;
3. when the forming environment of the source rock of the salinized lake basin is in the high salinity source rock (equivalent to boron more than 500 multiplied by 10)-6) The hydrocarbon output tended to decrease and then increase as salinity increased, decreasing from 15.69mg/g.rock to about 5.54mg/g.rock and then increasing to 9.92 mg/g.rock.
The fitting formula of equivalent boron content and hydrocarbon discharge amount is as follows:
y＝1E-06x2-0.0067x +14.483, R2 ═ 0.0778, y is the hydrocarbon displacement and x is the equivalent boron content.
Therefore, referring to fig. 6, it can be determined that the hydrocarbon discharge amount of the lamellar tuff dolomites and the tuff mudstones is large when the lower limit of the source rocks of the salination lake basin is 1.2% of TOC according to the salinity difference and the abundance of the organic matter.
An embodiment of the present invention provides a specific implementation of a dessert region prediction apparatus for a salty lake basin compact oil source rock, which can implement all the contents in the dessert region prediction method for a salty lake basin compact oil source rock, and referring to fig. 7, the dessert region prediction apparatus for a salty lake basin compact oil source rock specifically includes the following contents:
the device comprises a collecting unit 10, a calculating unit and a processing unit, wherein the collecting unit is used for collecting samples of the compact oil source rocks of the salinization lake basin and determining a plurality of evaluation parameters of the samples;
the characteristic unit 20 is configured to determine a hydrocarbon discharge characteristic corresponding to the sample of the compact oil source rock of the salinization lake basin;
a target parameter unit 30 for performing cluster analysis based on the hydrocarbon discharge characteristics and a plurality of evaluation parameters to determine a target parameter of the sample;
the quantitative unit 40 is used for determining a quantitative index corresponding to the target parameter according to a trend line between the target parameter and the hydrocarbon discharge characteristic;
and the prediction unit 50 is used for determining the sweet spot of the salty lake basin compact oil source rock according to the quantitative index.
Wherein the feature unit 20 includes:
the measuring subunit is used for carrying out organic carbon measurement on the sample of the compact oil source rock of the salinization lake basin to obtain the content of organic carbon;
the calculation unit is used for calculating the hydrocarbon generation characteristics and the hydrocarbon stagnation characteristics corresponding to the samples of the compact oil source rocks of the salinization lake basin according to the content of the organic carbon;
a characteristic subunit for determining the hydrocarbon expulsion characteristic based on the hydrocarbon production characteristic and the hydrocarbon stagnation characteristic.
Wherein the hydrocarbon discharge characteristic is the hydrocarbon discharge efficiency of the compact oil source rock of the salinization lake basin.
Wherein the target parameter unit 30 includes:
the clustering subunit is used for clustering a plurality of evaluation parameters by using the hydrocarbon discharge efficiency of the compact oil source rock of the salinization lake basin as a clustering center and adopting a k-means clustering algorithm to obtain a clustering parameter classification set;
and the target parameter subunit is used for determining the evaluation parameters in the clustering parameter classification set as target parameters.
Wherein the quantifying unit 40 includes:
a target value subunit, configured to determine a target value corresponding to the hydrocarbon discharge characteristic;
a quantitative value subunit, configured to determine, on the trend line, a quantitative value of the target parameter corresponding to the target value corresponding to the hydrocarbon discharge characteristic;
and the quantitative subunit is used for determining the quantitative value of the target parameter as the quantitative index.
Wherein, still include:
a classification unit 60 configured to determine an equivalent boron content of the sample, and classify the sample according to the equivalent boron content;
salinity unit 70 for determining the salinity corresponding to each classification.
The embodiment of the dessert region prediction device for the salty lake basin compact oil source rock provided by the invention can be specifically used for executing the processing flow of the embodiment of the dessert region prediction method for the salty lake basin compact oil source rock in the embodiment, and the functions of the processing flow are not described herein again, and reference can be made to the detailed description of the method embodiment.
As can be seen from the above description, the sweet spot prediction apparatus for the salty lake basin compact oil source rock provided by the embodiment of the present invention collects a sample of the salty lake basin compact oil source rock and determines a plurality of evaluation parameters of the sample; determining the hydrocarbon discharge characteristics corresponding to the sample of the compact oil source rock of the salinization lake basin; performing cluster analysis based on the hydrocarbon expulsion features and a plurality of evaluation parameters to determine target parameters of the sample; determining a quantitative index corresponding to the target parameter according to a trend line between the target parameter and the hydrocarbon discharge characteristic; determining a dessert area of the compact oil source rock of the salinization lake basin according to the quantitative index; the method can predict the dessert region of the salted compact oil, improves the accuracy of determination prediction, and enables the determination prediction of the desert region of the salted lake basin compact oil to be accurate and scientific.
The application provides an embodiment of an electronic device for implementing all or part of contents in a dessert region prediction method of a salty lake basin compact oil source rock, and the electronic device specifically includes the following contents:
a processor (processor), a memory (memory), a communication Interface (Communications Interface), and a bus; the processor, the memory and the communication interface complete mutual communication through the bus; the communication interface is used for realizing information transmission between related devices; the electronic device may be a desktop computer, a tablet computer, a mobile terminal, and the like, but the embodiment is not limited thereto. In this embodiment, the electronic device may be implemented with reference to the embodiment of the method for predicting the sweet spot region of the salty lake basin compact oil source rock and the embodiment of the device for predicting the sweet spot region of the salty lake basin compact oil source rock, which are incorporated herein and repeated in this embodiment.
Fig. 8 is a schematic block diagram of a system configuration of an electronic device 9600 according to an embodiment of the present application. As shown in fig. 8, the electronic device 9600 can include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. Notably, this FIG. 8 is exemplary; other types of structures may also be used in addition to or in place of the structure to implement telecommunications or other functions.
In one embodiment, the sweet spot prediction function of the saltating lake basin tight source rock may be integrated into the central processor 9100. The central processor 9100 may be configured to control as follows:
collecting a sample of the compact oil source rock of the salinization lake basin and determining a plurality of evaluation parameters of the sample; determining the hydrocarbon discharge characteristics corresponding to the sample of the compact oil source rock of the salinization lake basin; performing cluster analysis based on the hydrocarbon expulsion features and a plurality of evaluation parameters to determine target parameters of the sample; determining a quantitative index corresponding to the target parameter according to a trend line between the target parameter and the hydrocarbon discharge characteristic; and determining the dessert area of the compact oil source rock of the salinized lake basin according to the quantitative index.
In another embodiment, the sweet spot prediction apparatus for the salty lake basin compact oil source rock may be configured separately from the central processor 9100, for example, the sweet spot prediction apparatus for the salty lake basin compact oil source rock may be configured as a chip connected to the central processor 9100, and the sweet spot prediction function for the salty lake basin compact oil source rock is realized through the control of the central processor.
As shown in fig. 8, the electronic device 9600 may further include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is noted that the electronic device 9600 also does not necessarily include all of the components shown in fig. 8; further, the electronic device 9600 may further include components not shown in fig. 8, which may be referred to in the art.
As shown in fig. 8, a central processor 9100, sometimes referred to as a controller or operational control, can include a microprocessor or other processor device and/or logic device, which central processor 9100 receives input and controls the operation of the various components of the electronic device 9600.
The memory 9140 can be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information relating to the failure may be stored, and a program for executing the information may be stored. And the central processing unit 9100 can execute the program stored in the memory 9140 to realize information storage or processing, or the like.
The input unit 9120 provides input to the central processor 9100. The input unit 9120 is, for example, a key or a touch input device. Power supply 9170 is used to provide power to electronic device 9600. The display 9160 is used for displaying display objects such as images and characters. The display may be, for example, an LCD display, but is not limited thereto.
The memory 9140 can be a solid state memory, e.g., Read Only Memory (ROM), Random Access Memory (RAM), a SIM card, or the like. There may also be a memory that holds information even when power is off, can be selectively erased, and is provided with more data, an example of which is sometimes called an EPROM or the like. The memory 9140 could also be some other type of device. Memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application/function storage portion 9142, the application/function storage portion 9142 being used for storing application programs and function programs or for executing a flow of operations of the electronic device 9600 by the central processor 9100.
The memory 9140 can also include a data store 9143, the data store 9143 being used to store data, such as contacts, digital data, pictures, sounds, and/or any other data used by an electronic device. The driver storage portion 9144 of the memory 9140 may include various drivers for the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging applications, contact book applications, etc.).
The communication module 9110 is a transmitter/receiver 9110 that transmits and receives signals via an antenna 9111. The communication module (transmitter/receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, which may be the same as in the case of a conventional mobile communication terminal.
Based on different communication technologies, a plurality of communication modules 9110, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, may be provided in the same electronic device. The communication module (transmitter/receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide audio output via the speaker 9131 and receive audio input from the microphone 9132, thereby implementing ordinary telecommunications functions. The audio processor 9130 may include any suitable buffers, decoders, amplifiers and so forth. In addition, the audio processor 9130 is also coupled to the central processor 9100, thereby enabling recording locally through the microphone 9132 and enabling locally stored sounds to be played through the speaker 9131.
Embodiments of the present invention also provide a computer-readable storage medium capable of implementing all steps in the dessert region prediction method for the salty lake basin compact oil source rock in the above embodiments, where the computer-readable storage medium stores thereon a computer program that, when executed by a processor, implements all steps of the dessert region prediction method for the salty lake basin compact oil source rock in the above embodiments, for example, the processor implements the following steps when executing the computer program:
collecting a sample of the compact oil source rock of the salinization lake basin and determining a plurality of evaluation parameters of the sample; determining the hydrocarbon discharge characteristics corresponding to the sample of the compact oil source rock of the salinization lake basin; performing cluster analysis based on the hydrocarbon expulsion features and a plurality of evaluation parameters to determine target parameters of the sample; determining a quantitative index corresponding to the target parameter according to a trend line between the target parameter and the hydrocarbon discharge characteristic; and determining the dessert area of the compact oil source rock of the salinized lake basin according to the quantitative index.
Although the present invention provides method steps as described in the examples or flowcharts, more or fewer steps may be included based on routine or non-inventive labor. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an actual apparatus or client product executes, it may execute sequentially or in parallel (e.g., in the context of parallel processors or multi-threaded processing) according to the embodiments or methods shown in the figures.
As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, apparatus (system) or computer program product. Accordingly, embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment. In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict. The present invention is not limited to any single aspect, nor is it limited to any single embodiment, nor is it limited to any combination and/or permutation of these aspects and/or embodiments. Moreover, each aspect and/or embodiment of the present invention may be utilized alone or in combination with one or more other aspects and/or embodiments thereof.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.

Claims (15)

1. A method for predicting a sweet spot of a salty lake basin compact oil source rock is characterized by comprising the following steps:
collecting a sample of the compact oil source rock of the salinization lake basin and determining a plurality of evaluation parameters of the sample;
determining the hydrocarbon discharge characteristics corresponding to the sample of the compact oil source rock of the salinization lake basin;
performing cluster analysis based on the hydrocarbon expulsion features and a plurality of evaluation parameters to determine target parameters of the sample;
determining a quantitative index corresponding to the target parameter according to a trend line between the target parameter and the hydrocarbon discharge characteristic;
and determining the dessert area of the compact oil source rock of the salinized lake basin according to the quantitative index.
2. The method for predicting the sweet spot of the saltating lake basin tight source oil rock according to claim 1, further comprising, after the collecting the sample of the saltating lake basin tight source oil rock:
determining the equivalent boron content of the sample, and classifying the sample according to the equivalent boron content;
and determining the salinity corresponding to each classification.
3. The method of predicting a sweet spot of a brackish lake basin compact oil source rock according to claim 1, wherein the plurality of evaluation parameters comprises: salinity, organic carbon content, soluble hydrocarbon content, pyrolytic hydrocarbon content, peak top temperature, organic matter abundance, mineral content and source rock thermal evolution maturity.
4. The method for predicting the sweet spot of the saltating lake basin compact oil source rock according to claim 1, wherein the determining the hydrocarbon discharge characteristics corresponding to the sample of the saltating lake basin compact oil source rock comprises:
performing organic carbon determination on the sample of the compact oil source rock of the salinization lake basin to obtain the content of organic carbon;
calculating hydrocarbon generation characteristics and hydrocarbon stagnation characteristics corresponding to the samples of the compact oil source rocks of the salinization lake basin according to the content of the organic carbon;
determining the hydrocarbon expulsion characteristics based on the hydrocarbon production characteristics and the stagnant hydrocarbon characteristics.
5. The method of predicting the sweet spot of a saltating lake basin tight source of oil rock of claim 4, wherein the hydrocarbon discharge characteristic is the hydrocarbon discharge efficiency of the saltating lake basin tight source of oil rock.
6. The method of predicting the sweet spot of the saltating lake basin compact oil source rock according to claim 5, wherein the determining the target parameters of the sample by performing cluster analysis based on the hydrocarbon discharge characteristics and a plurality of evaluation parameters comprises:
clustering a plurality of evaluation parameters by using the hydrocarbon discharge efficiency of the compact oil source rock of the salinization lake basin as a clustering center by adopting a k-means clustering algorithm to obtain a clustering parameter classification set;
and determining the evaluation parameters in the clustering parameter classification set as target parameters.
7. The method for predicting the sweet spot of the salty lake basin compact oil source rock according to claim 5, wherein the determining the quantitative index corresponding to the target parameter according to the trend line between the target parameter and the hydrocarbon discharge characteristic comprises:
determining a target value corresponding to the hydrocarbon discharge characteristic;
determining a quantitative value of the target parameter corresponding to a target value corresponding to the hydrocarbon discharge characteristic on the trend line;
and determining the quantitative value of the target parameter as the quantitative index.
8. A device for predicting a sweet spot of a salty lake basin compact oil source rock, comprising:
the system comprises a collecting unit, a processing unit and a processing unit, wherein the collecting unit is used for collecting a sample of the compact oil source rock of the salinization lake basin and determining a plurality of evaluation parameters of the sample;
the characteristic unit is used for determining the hydrocarbon discharge characteristics corresponding to the sample of the compact oil source rock of the salinization lake basin;
a target parameter unit for performing cluster analysis based on the hydrocarbon discharge characteristics and a plurality of evaluation parameters to determine a target parameter of the sample;
the quantitative unit is used for determining a quantitative index corresponding to the target parameter according to a trend line between the target parameter and the hydrocarbon discharge characteristic;
and the prediction unit is used for determining the sweet spot of the compact oil source rock of the salinized lake basin according to the quantitative index.
9. The apparatus of claim 8, further comprising:
the classification unit is used for determining the equivalent boron content of the sample and classifying the sample according to the equivalent boron content;
and the salinity unit is used for determining the salinity corresponding to each classification.
10. The apparatus of claim 8, wherein the characterization unit comprises:
the measuring subunit is used for carrying out organic carbon measurement on the sample of the compact oil source rock of the salinization lake basin to obtain the content of organic carbon;
the calculation unit is used for calculating the hydrocarbon generation characteristics and the hydrocarbon stagnation characteristics corresponding to the samples of the compact oil source rocks of the salinization lake basin according to the content of the organic carbon;
a characteristic subunit for determining the hydrocarbon expulsion characteristic based on the hydrocarbon production characteristic and the hydrocarbon stagnation characteristic.
11. The apparatus of claim 10, wherein the hydrocarbon expulsion characteristic is the hydrocarbon expulsion efficiency of the saltating lake basin compact source oil rock.
12. The apparatus of claim 11, wherein the target parameter unit comprises:
the clustering subunit is used for clustering a plurality of evaluation parameters by using the hydrocarbon discharge efficiency of the compact oil source rock of the salinization lake basin as a clustering center and adopting a k-means clustering algorithm to obtain a clustering parameter classification set;
and the target parameter subunit is used for determining the evaluation parameters in the clustering parameter classification set as target parameters.
13. The apparatus of claim 11, wherein the quantification unit comprises:
a target value subunit, configured to determine a target value corresponding to the hydrocarbon discharge characteristic;
a quantitative value subunit, configured to determine, on the trend line, a quantitative value of the target parameter corresponding to the target value corresponding to the hydrocarbon discharge characteristic;
and the quantitative subunit is used for determining the quantitative value of the target parameter as the quantitative index.
14. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the method of predicting a sweet spot of a brackish lake basin tight oil source rock of any one of claims 1 to 7.
15. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method for predicting a sweet spot of a brackish lake basin compact oil source rock according to any one of claims 1 to 7.
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