WO2017024530A1 - Procédé permettant de calculer la teneur en carbone organique d'une roche mère d'hydrocarbures - Google Patents

Procédé permettant de calculer la teneur en carbone organique d'une roche mère d'hydrocarbures Download PDF

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WO2017024530A1
WO2017024530A1 PCT/CN2015/086673 CN2015086673W WO2017024530A1 WO 2017024530 A1 WO2017024530 A1 WO 2017024530A1 CN 2015086673 W CN2015086673 W CN 2015086673W WO 2017024530 A1 WO2017024530 A1 WO 2017024530A1
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log
index
density
calculating
curve
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PCT/CN2015/086673
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赵龙
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深圳朝伟达科技有限公司
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Priority to PCT/CN2015/086673 priority Critical patent/WO2017024530A1/fr
Priority to PCT/CN2015/096202 priority patent/WO2017024700A1/fr
Publication of WO2017024530A1 publication Critical patent/WO2017024530A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
    • G01V11/00—Prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00

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  • the invention relates to the field of petroleum geological exploration, in particular to a method for calculating the content of organic carbon in a source rock.
  • the source rock is also called the source rock. It is a rock rich in organic matter, massively producing oil and gas and discharging oil and gas. In order to extract a large amount of oil and gas, it is necessary to accurately identify the source rock.
  • organic matter abundance is one of the important parameters for evaluating the hydrocarbon generation of hydrocarbon source rocks, and the organic carbon content is the main indicator reflecting the abundance of organic matter in source rocks. Therefore, the method for calculating the organic carbon content in source rocks has been widely attention.
  • the process of calculating the organic carbon content in the source rock is specifically: the resistivity log and the acoustic time difference log measured in the field. Based on the resistivity log curve and the acoustic time difference log, a weighted average of the difference between the resistivity and the acoustic time difference is calculated. The calculated weighted average is calibrated with geochemical analysis data as the organic carbon content of the source rock.
  • the acoustic time difference log and resistivity log are affected by lithology, hydrocarbon content and pore structure. Therefore, when calculating the organic carbon content according to the above method, the calculation accuracy is reduced.
  • embodiments of the present invention provide a method and apparatus for calculating the content of organic carbon in a source rock.
  • the technical solution is as follows:
  • a method of calculating an organic carbon content in a source rock comprising:
  • the calculating a lithology index of the sand mudstone according to the neutron log curve, the density log curve, and the acoustic wave time difference log curve including:
  • the lithology index of the sand mudstone is calculated according to the porphyrite neutron porosity index, the ash limestone density porosity index and the ash limestone acoustic porosity index.
  • the calculating a lithology index of the sandstone rock according to the porphyrite neutron porosity index, the ash limestone density porosity index, and the limestone acoustic wave porosity index including:
  • a lithology index of the sand mudstone is calculated based on the first difference, the second difference, and the third difference.
  • the identifying the source rock from the sandstone mudstone according to the first shale content indication, the second shale content indication, and the lithology index including:
  • the selected rock formation is identified as a source rock.
  • calculating the organic carbon content in the source rock according to the density log curve, the acoustic wave time difference log curve, and the resistivity log curve including:
  • TOC is the organic carbon content in the source rock
  • Rt is the resistivity value in the resistivity log
  • ⁇ t is the acoustic time difference in the acoustic time difference log
  • ⁇ For the density values in the density log, a, b, and c are known coefficients.
  • an apparatus for calculating an organic carbon content in a source rock comprising:
  • a first calculation module configured to calculate a first shale content indication according to the natural potential logging curve
  • a second calculation module configured to calculate a second shale content indication according to the natural gamma log curve
  • a third calculation module is configured to calculate a lithology index of the sand mudstone according to the neutron log curve, the density log curve, and the acoustic time difference log;
  • An identification module for indicating, according to the first shale content indicator, the second shale content indicator, and the lithology index, Identifying source rocks from the sandstone;
  • a fourth calculating module configured to calculate an organic carbon content in the source rock according to the density logging curve, the acoustic wave time difference logging curve, and the resistivity logging curve.
  • the third calculating module includes:
  • a first calculating unit configured to calculate a neutron porosity index of the limestone according to the neutron log curve
  • a second calculating unit configured to calculate a limestone density porosity index according to the density logging curve
  • a third calculating unit configured to calculate a limestone acoustic wave porosity index according to the acoustic wave time difference logging curve
  • a fourth calculating unit configured to calculate a lithology index of the sand mudstone according to the porphyrite neutron porosity index, the ash limestone density porosity index, and the ash limestone acoustic porosity index.
  • the fourth calculating unit includes:
  • a first calculating subunit configured to calculate a first difference between the porphyrite neutron porosity index and the ash lime density porosity index
  • a second calculating subunit configured to calculate a second difference between the porphyrite neutron porosity index and the ash lime sound porosity index
  • a third calculating subunit configured to calculate a third difference between the apparent limestone density porosity index and the apparent limestone acoustic wave porosity index
  • a fourth calculating subunit configured to calculate a lithology index of the sand mudstone according to the first difference value, the second difference value, and the third difference value.
  • the identifying module includes:
  • a selection unit configured to select, from the sand mudstone, the rock formation indicating that the first shale content indicates is greater than a first threshold, the second shale content indicates greater than a second threshold, and the lithology index is greater than a third threshold;
  • a determining unit for determining the selected rock formation as a source rock is
  • the fourth calculation module includes:
  • a fifth calculating unit configured to calculate an organic carbon content in the source rock according to the density log, the acoustic time difference log, and the resistivity log according to the following formula
  • TOC is the organic carbon content in the source rock
  • Rt is the resistivity value in the resistivity log
  • ⁇ t is the acoustic time difference in the acoustic time difference log
  • ⁇ For the density values in the density log, a, b, and c are known coefficients.
  • the first shale content indication is calculated based on the natural potential log. Natural gamma
  • the well curve calculates an indication of the second shale content.
  • the lithology index of the sand mudstone is calculated.
  • the source rock can be identified from the sandstone mudstone.
  • the organic carbon content in the source rock is calculated based on the density log, the acoustic time difference log and the resistivity log.
  • FIG. 1 is a flow chart of a method for calculating an organic carbon content in a source rock according to a first embodiment of the present invention
  • FIG. 2 is a flow chart of a method for calculating organic carbon content in a source rock according to a second embodiment of the present invention
  • FIG. 3 is a schematic view showing a comparison result between a calculated value and an analysis value of an organic carbon content in a source rock according to a second embodiment of the present invention
  • FIG. 4 is a schematic structural view of an apparatus for calculating an organic carbon content in a source rock according to a third embodiment of the present invention.
  • the source rock is usually mudstone or shale, which is a type of sedimentary rock with a particle diameter of less than 1/256 mm.
  • the mudstone has a massive structure
  • the shale has a bedding structure.
  • the composition and the particle size There is no strict difference between the composition and the particle size.
  • the two are collectively referred to as source rocks.
  • most of the source rocks are fine-grained sedimentary rocks dominated by mudstones and shale.
  • the most characteristic of such rocks is the richness of organic matter and poor connectivity of pores, especially the fine pore size.
  • the permeability of the rock is very low, so the source rock is still the most common barrier or cap.
  • mudstone or shale is a source rock, which is a place where oil or natural gas is generated.
  • sandstone and conglomerate with larger particle size have a lower proportion in sedimentary rock strata, but due to their good pore connectivity, the pore size is relatively large and the permeability is high.
  • Organic matter and clay minerals are two major components of argillaceous source rocks. Among them, organic matter is often present in clay minerals in the form of dispersion, bedding enrichment, local enrichment, and biological residues. Organic matter and clay minerals are two important components that contribute to the log response of source rock. Logging is the difference between the physical and electrochemical properties of the organic matter and clay minerals in the rock, such as the type, abundance, compaction degree, enrichment state, mature evolution and fluid composition filled in the pores. The well curve identifies and evaluates the theoretical basis of the source rock.
  • kerogen is the main body of organic matter in source rocks. Although kerogen is an organic matter in source rocks, it is separated from the inorganic minerals coexisting with it, which does not reflect the occurrence and difference of organic matter. What is the type of organic matter? Laboratory cracking analysis shows that the organic matter present in the sedimentary rock consists mainly of two parts, the soluble organic matter and the insoluble organic matter (kerogen), which together form an organically connected whole, which together reflect the surface of the deposited organic matter. The soluble organic matter is chemically bonded to the clay mineral.
  • FIG. 1 is a flow chart of a method for calculating organic carbon content in a source rock according to an embodiment of the present invention. Referring to Figure 1, the method includes:
  • Step 101 Calculate the first shale content indication according to the natural potential logging curve.
  • Step 102 Calculate a second shale content indication according to the natural gamma log curve.
  • Step 103 Calculate the lithology index of the sand mudstone according to the neutron log curve, the density log curve and the acoustic wave time difference log curve.
  • Step 104 Identify the source rock from the sandstone mudstone according to the first shale content indication, the second shale content indication, and the lithology index.
  • Step 105 Calculate the organic carbon content in the source rock according to the density log curve, the acoustic wave time difference log curve and the resistivity log curve.
  • the first shale content indication is calculated based on the natural potential log.
  • a second shale content indicator is calculated based on the natural gamma log curve.
  • the source rock can be identified from the sandstone mudstone.
  • the organic carbon content in the source rock is calculated based on the density log, the acoustic time difference log and the resistivity log.
  • the lithology index of the sandstone rock is calculated according to the neutron log curve, the density log curve, and the acoustic time difference log, including:
  • the lithology index of sand-shale rock is calculated according to the neutron porosity index, the limestone density porosity index and the ashes limestone acoustic porosity index.
  • the lithology index of the sand-shale rock is calculated according to the ash neutron porosity index, the apparent limestone density porosity index, and the apparent limestone acoustic porosity index, including:
  • the lithology index of the sand mudstone is calculated based on the first difference, the second difference, and the third difference.
  • the source rock is identified from the sandstone mudstone according to the first shale content indication, the second shale content indicator, and the lithology index, including:
  • the selected rock formation is identified as a source rock.
  • the organic carbon content in the source rock is calculated based on the density log curve, the acoustic time difference log, and the resistivity log, including:
  • the organic carbon content in the source rock is calculated according to the following formula
  • TOC is the organic carbon content in the source rock
  • Rt is the resistivity value in the resistivity log
  • ⁇ t is the acoustic time difference in the acoustic time log
  • ⁇ is in the density log.
  • Density values, a, b, and c are known coefficients.
  • FIG. 2 is a flow chart of a method for calculating the content of organic carbon in a source rock according to an embodiment of the present invention. Referring to Figure 2, the method includes:
  • Step 201 Calculate the first shale content indication according to the natural potential logging curve.
  • the first shale content indication is calculated according to the following formula (1);
  • I SP is the first shale content indication
  • SP max is the amplitude of the natural potential on the pure sandstone
  • SP min is the baseline value of the natural potential on the mudstone layer
  • SP is the natural potential measurement.
  • the permeability of the sandstone layer is relatively good, showing a significant difference in the natural potential logging curve. Therefore, when the salinity of the formation water is stable on the well profile, the natural potential can be used.
  • the relative amplitude difference defines the shale content indication of the natural potential log, such as the formula for the first shale content indication described above.
  • the natural potential logging curve is a curve in which the natural potential changes with the depth of the well.
  • Step 202 Calculate a second shale content indication according to the natural gamma log curve.
  • the second shale content indication is calculated according to the following formula (2);
  • I GR is the second shale content indication
  • GR max is the amplitude of the natural gamma on the mudstone layer
  • GR min is the baseline value of the natural gamma on the pure sandstone layer
  • GR is Natural gamma log values on natural gamma logs.
  • I GR value is larger, it indicates that the muddy content in the rock formation is larger, and conversely, when the I GR value is smaller, the muddy content in the rock formation is indicated to be smaller.
  • the hydrocarbon source rock layer is generally rich in carbon, which can adsorb more radioactive elements, such as the adsorption of special element uranium, so that the source rock shows high anomaly on the natural gamma log curve, so natural gamma logging can be utilized. Curve to identify source rocks.
  • the uranium content is not only related to the abundance of organic matter, but also affected by the distribution of cracks. Therefore, if the natural gamma log is used alone to identify the source rock, the accuracy will be reduced.
  • the relative magnitude of the natural gamma log can indicate the amount of shale content, so the second mud can be defined based on the natural gamma log curve.
  • the formula for the quality content indication can indicate the amount of shale content, so the second mud can be defined based on the natural gamma log curve.
  • the natural gamma log curve is the intensity of the gamma ray emitted during the decay of the naturally occurring radionuclide in the well, and the natural gamma log curve is also a curve that varies with the depth of the well.
  • Step 203 Calculate the lithology index of the sand mudstone according to the neutron log curve, the density log curve, and the acoustic wave time difference log curve.
  • this step can be implemented according to the following steps (1)-(4), including:
  • the porphyrite porosity index of the limestone is calculated according to the following formula (3);
  • CNL ma is the neutron porosity response of the limestone skeleton
  • CNL f is the neutron porosity response of the formation water
  • CNL is the neutron log on the neutron log value.
  • the limestone skeleton is a non-porous limestone.
  • the neutron log mainly responds to the hydrogen index in the formation, and its magnitude is proportional to the hydrogen content in the formation.
  • the neutron response of the pure sandstone reservoir segment basically reflects the reservoir porosity
  • the neutron response mainly reflects the bound water porosity of the mudstone.
  • a weighted average of the volume fractions of the two Since the mudstone layer contains large bound water porosity, a log response larger than that of the sandstone reservoir will appear on the measured curve. Therefore, the above formula for the neutron porosity index of the limestone can be defined.
  • the apparent limestone density porosity index is calculated according to the following formula (4);
  • DEN ma is the density value of the limestone skeleton
  • DEN f is the density value of the formation water
  • DEN is the density log value on the density log.
  • the density logging mainly reflects the electron density of the gamma ray in the stratum, which approximates the stratum.
  • the density is proportional.
  • the density of the pure sandstone reservoir section basically reflects the reservoir porosity.
  • the density porosity is significantly smaller than the bound water porosity of the actual formation, so the above formula for the density of the limestone density can be defined.
  • the limestone acoustic wave porosity index is calculated according to the following formula (5);
  • AC f is the acoustic wave time difference response value of the formation water
  • AC ma is the acoustic wave time difference response value of the limestone skeleton
  • AC is the acoustic wave time difference logging value on the acoustic wave time difference logging curve.
  • the acoustic time difference log mainly reflects the propagation of longitudinal waves in the formation, and its size is related to the lithology and porosity of the skeleton in the formation.
  • the acoustic time difference in the well-knotted pure sandstone reservoir section basically reflects the reservoir porosity
  • the acoustic time difference is the comprehensive response of the shale type, distribution mode and bound water porosity. Since the mudstone layer contains large bound water porosity, there is a larger acoustic time difference than the sandstone reservoir on the measured curve. Therefore, the above formula for the limestone acoustic wave porosity index can be defined.
  • a first difference between the ash neutron porosity index and the ash lime density porosity index is calculated.
  • the lithology index of the sand mudstone is calculated based on the first difference, the second difference, and the third difference.
  • the lithology index of the sand mudstone is calculated according to the following formula (6);
  • I lith is a lithology index
  • the first value is the sum of the porosity and density of the neutron-looking limestone in the pure sandstone section and the porosity of the limestone
  • the second value is the neutron-looking limestone pore of the mudstone section.
  • Degree and density are the sum of the limestone porosity.
  • I lith is small for the pure sandstone reservoir, close to 0, and I lith is larger for the shale segment and close to 1.
  • the first difference, the second difference, and the third difference are all positive numbers, that is, the absolute value of the difference.
  • the porphyrite, density and sound wave three ash limestone porosity can reflect the actual porosity of the reservoir.
  • the porphyrite porosity of the neutron and sound waves will be much larger than the density of the limestone. Therefore, using the difference between the two ash limestone porosity, an index for identifying the lithology of the reservoir can be constructed to divide the shale section.
  • Step 204 Select a rock formation from the sand mudstone that indicates that the first shale content indicates greater than the first threshold, the second shale content indicates greater than the second threshold, and the lithology index is greater than the third threshold.
  • the first threshold, the second threshold, and the third threshold are all set in advance, and are not specifically limited in this embodiment of the present invention.
  • Step 206 Determine the selected rock formation as a source rock.
  • the source rocks are mainly mudstones and shale, as well as coal-series source rocks.
  • the coal-based source rocks are characterized by “three highs and three lows” on the logging curve, ie, high neutrons, high acoustic time difference, high resistivity, low density, low natural potential, low natural gamma (due to coal seam radioactivity) weak). Therefore, the first difference, the second difference, and the third difference described above cannot be used for the identification of coal-based source rocks.
  • the difference between the resistivity of the coal-bearing formation and the resistivity of the aqueous reservoir can be utilized, and naturally The characteristics of radioactive polar and low density identify coal-series source rocks.
  • carbonaceous mudstone and dark mudstone may be included.
  • the logging response of carbonaceous mudstone and dark mudstone is characterized by “five high and one low”, namely high neutron, high acoustic time difference, high electrical resistivity (higher than surrounding rock mudstone), high natural gamma, high uranium content, low density.
  • the layer with high organic carbon content has a relatively high natural gamma and uranium curve value. Therefore, in addition to using several indicators of the above analysis, it is necessary to separately establish other discriminant indicators to identify carbonaceous mudstone and dark mudstone.
  • the organic carbon content in the source rock can be calculated according to the following steps.
  • Step 207 Calculate the organic carbon content in the source rock according to the density log curve, the acoustic time difference log and the resistivity log.
  • the organic carbon content in the source rock is calculated according to the following formula (7);
  • TOC is the organic carbon content in the source rock
  • Rt is the resistivity value in the resistivity log
  • ⁇ t is the acoustic time difference in the acoustic time difference log
  • ⁇ is the density measurement
  • the density values in the well curve, a, b and c are known coefficients.
  • the organic source-rich source rock has a low density
  • the density log measures the bulk density of the formation, including the skeleton density and the fluid density.
  • the density of organic matter in the source rock (1.03 ⁇ 1.1g/cm 3 ) is significantly lower than the density of the surrounding rock matrix (the density of the clay skeleton is 2.3-3.1g/cm 3 ), which reduces the log value of the source rock density.
  • the change of formation density has a certain correspondence with the change of organic matter abundance.
  • the density calculation curve can be used to correct the calculation formula of the organic carbon content.
  • the acoustic time difference log is also the sonic log, so ⁇ t is the acoustic time difference in the acoustic time difference log.
  • the three parameters a, b and c can be obtained by the least squares fitting after collecting samples from the study area system, and in order to accurately obtain the values of a, b and c, the mudstone cores can be selected. The regression analysis is performed on the well sections with long and TOC analysis data and corresponding depths.
  • the baseline is mentioned in the above description.
  • the determination method of the baseline may be: the acoustic wave time difference logging curve adopts arithmetic coordinates, and the resistivity logging curve adopts logarithmic coordinates, when the two logging curves are parallel in a certain depth or When overlapping, the log curve within this depth is determined as the baseline.
  • the response of the logging curve to the difference between the organic carbon content of the rock formation and the physical properties of the filled pore fluid is the basis for identifying and evaluating the source rock using the logging curve.
  • the higher the organic carbon content the greater the anomaly on the log, and the abnormal value can be used to calculate the organic carbon content.
  • the rock is characterized by organic rocks. Due to the special physical properties of the dispersed organic kerogen, such as its poor conductivity, strong natural radioactivity, density close to water density, and light components, the acoustic time difference is close to 550 ⁇ s/m and the hydrogen content is close to 67%.
  • the good oil-bearing rock has an organic carbon TOC content of nearly 30%, which is clearly reflected in the log curve, while the poor oil-bearing rock has an organic carbon TOC content of less than 30%. Obvious anomaly, but it can still be reflected. Therefore, in the embodiment of the present invention, the above-mentioned logging curve can be used to calculate the organic carbon content in the source rock.
  • the source rocks are classified into high quality, medium and poor according to the organic carbon content.
  • TOC ⁇ 2% is a high-quality source rock
  • 1% ⁇ TOC ⁇ 2% is a medium source rock
  • 0.3% ⁇ TOC ⁇ 1% is a poor source rock.
  • the continuous curve from the TOC is calculated according to the method provided by the embodiment of the present invention.
  • the curve of the organic carbon content, while the horizontal short line on the TOC curve is the organic carbon content obtained by geochemical analysis. It can be seen that the organic carbon content calculated by the method provided by the embodiment of the present invention is in good agreement with the geochemical analysis value of the high organic carbon content layer. Therefore, the method provided by the embodiment of the present invention has different organic carbon content. The source rock can also achieve better results.
  • the first shale content indication is calculated based on the natural potential log.
  • a second shale content indicator is calculated based on the natural gamma log curve.
  • the source rock can be identified from the sandstone mudstone.
  • the organic carbon content in the source rock is calculated based on the density log, the acoustic time difference log and the resistivity log.
  • the device includes: a first calculation module 401, a second calculation module 402, a third calculation module 403, an identification module 404, and a fourth calculation module 405;
  • a first calculating module 401 configured to calculate a first shale content indication according to the natural potential logging curve
  • a second calculation module 402 configured to calculate a second shale content indication according to the natural gamma log curve
  • a third calculation module 403, configured to calculate a lithology index of the sand mudstone according to the neutron log curve, the density log curve, and the acoustic time difference log;
  • the identification module 404 is configured to identify the source rock from the sandstone mudstone according to the first shale content indication, the second shale content indication, and the lithology index;
  • the fourth calculation module 405 is configured to calculate the organic carbon content in the source rock according to the density log curve, the acoustic wave time difference log curve and the resistivity log curve.
  • the third calculating module 403 includes:
  • a first calculating unit configured to calculate a neutron porosity index of the limestone according to the neutron log curve
  • a second calculating unit configured to calculate a limestone density porosity index according to the density logging curve
  • a third calculating unit configured to calculate a limestone acoustic wave porosity index according to the acoustic wave time difference logging curve
  • the fourth calculating unit is configured to calculate the lithology index of the sand-shale rock according to the porphyrite porosity index, the limestone density porosity index and the apparent limestone acoustic porosity index.
  • the fourth calculating unit comprises:
  • a first calculating subunit for calculating a first difference between the ash neutron porosity index and the apparent limestone density porosity index
  • a second calculating subunit for calculating a second difference between the porphyrite porosity index of the limestone and the acoustic wave porosity index of the limestone;
  • a third calculating subunit for calculating a third difference between the apparent limestone density porosity index and the apparent limestone acoustic porosity index
  • a fourth calculating subunit configured to calculate a lithology index of the sand mudstone according to the first difference value, the second difference value, and the third difference value.
  • the identification module 404 includes:
  • a selection unit configured to select, from the sand mudstone, a formation having a first shale content indicating greater than a first threshold, a second shale content indicating greater than a second threshold, and a lithology index greater than a third threshold;
  • a determining unit for determining the selected rock formation as a source rock is
  • the fourth calculating module 405 includes:
  • a fifth calculating unit configured to calculate an organic carbon content in the source rock according to the density log, the acoustic time difference log, and the resistivity log;
  • TOC is the organic carbon content in the source rock
  • Rt is the resistivity value in the resistivity log
  • ⁇ t is the acoustic time difference in the acoustic time log
  • ⁇ is in the density log.
  • Density values, a, b, and c are known coefficients.
  • the first shale content indication is calculated based on the natural potential log.
  • a second shale content indicator is calculated based on the natural gamma log curve.
  • the source rock can be identified from the sandstone mudstone.
  • the organic carbon content in the source rock is calculated based on the density log, the acoustic time difference log and the resistivity log.
  • the device for calculating the organic carbon content in the source rock provided by the above embodiment is only illustrated by the division of the above functional modules when calculating the organic carbon content in the source rock.
  • the above function assignment is completed by different functional modules, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above.
  • the apparatus for calculating the organic carbon content in the source rock provided by the above embodiment is the same as the method embodiment for calculating the organic carbon content in the source rock. The specific implementation process is described in detail in the method embodiment, and details are not described herein again.
  • a person skilled in the art may understand that all or part of the steps of implementing the above embodiments may be completed by hardware, or may be instructed by a program to execute related hardware, and the program may be stored in a computer readable storage medium.
  • the storage medium mentioned may be a read only memory, a magnetic disk or an optical disk or the like.

Abstract

L'invention concerne un procédé permettant de calculer la teneur en carbone organique d'une roche mère d'hydrocarbures, appartenant au domaine de la prospection pétrolifère géologique. Le procédé comprend : le calcul d'une première indication de teneur en schiste selon une courbe de diagraphie potentielle naturelle (101) ; le calcul d'une seconde indication de teneur en schiste selon une courbe de diagraphie gamma naturelle (102) ; le calcul de l'indice lithologique du schiste sableux selon une courbe de diagraphie de neutrons, une courbe de diagraphie de densité et une courbe de diagraphie de temps de transit d'intervalle (103) ; la reconnaissance d'une roche mère d'hydrocarbures dans le schiste sableux selon la première indication de teneur en schiste, la seconde indication de teneur en schiste et l'indice lithologique (104) ; et le calcul de la teneur en carbone organique de la roche mère d'hydrocarbures selon la courbe de diagraphie de densité, la courbe de diagraphie de temps de transit d'intervalle et une courbe de diagraphie de résistivité (105). Le dispositif comprend : un premier module de calcul (401), un deuxième module de calcul (402), un troisième module de calcul (403), un module de reconnaissance (404) et un quatrième module de calcul (405). La précision du calcul de la teneur en carbone organique de la roche mère d'hydrocarbures est améliorée par le biais des multiples courbes de diagraphie.
PCT/CN2015/086673 2015-08-11 2015-08-11 Procédé permettant de calculer la teneur en carbone organique d'une roche mère d'hydrocarbures WO2017024530A1 (fr)

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PCT/CN2015/096202 WO2017024700A1 (fr) 2015-08-11 2015-12-02 Dispositif permettant de calculer la teneur en carbone organique d'une roche mère

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Cited By (26)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107798211A (zh) * 2017-10-17 2018-03-13 中国石油天然气股份有限公司 地下烃源岩层中有机质的有机酸生成量的确定方法和装置
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Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090254283A1 (en) * 2008-04-07 2009-10-08 Baker Hughes Incorporated method for petrophysical evaluation of shale gas reservoirs
CN102565104A (zh) * 2011-12-21 2012-07-11 中国石油天然气股份有限公司 一种烃源岩有机碳含量的测定方法
CN103792338A (zh) * 2014-01-28 2014-05-14 中国石油天然气股份有限公司 一种烃源岩有机碳含量的确定方法和装置
CN104237966A (zh) * 2014-09-02 2014-12-24 中国石油天然气股份有限公司 测算地下有机质孔隙度的方法和装置
CN104636588A (zh) * 2014-08-25 2015-05-20 中国石油天然气股份有限公司 计算烃源岩中有机碳含量的方法及装置

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104656162A (zh) * 2015-02-13 2015-05-27 西安石油大学 一种富铀烃源岩铀含量及有机碳含量确定方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090254283A1 (en) * 2008-04-07 2009-10-08 Baker Hughes Incorporated method for petrophysical evaluation of shale gas reservoirs
CN102565104A (zh) * 2011-12-21 2012-07-11 中国石油天然气股份有限公司 一种烃源岩有机碳含量的测定方法
CN103792338A (zh) * 2014-01-28 2014-05-14 中国石油天然气股份有限公司 一种烃源岩有机碳含量的确定方法和装置
CN104636588A (zh) * 2014-08-25 2015-05-20 中国石油天然气股份有限公司 计算烃源岩中有机碳含量的方法及装置
CN104237966A (zh) * 2014-09-02 2014-12-24 中国石油天然气股份有限公司 测算地下有机质孔隙度的方法和装置

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CN110619353A (zh) * 2019-08-22 2019-12-27 中国石油天然气集团有限公司 一种基于深度学习的多尺度测井曲线自动识别方法
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