A method for continuously characterizing the oil content distribution of mixed shale oil

Abstract

The present invention provides a method for continuously characterizing the oil content distribution of mixed shale oil, and belongs to the technical field of quantitative characterization of oil content of unconventional oil and gas. Conduct core porosity and oil content tests on mixed rock samples of different lithologies; select logging curves, and construct porosity interpretation models and clay interpretation models for mixed shale reservoirs according to different lithologies; construct porosity and clay interpretation models for mixed shale reservoirs based on the constructed different lithologies, determine rock electrical parameters for different lithologies, establish rock electrical parameter interpretation models, and establish saturation index interpretation models for different lithologies; invert formation water resistivity values ​​based on measured oil saturation data and rock electrical parameter interpretation models, and establish resistivity value interpretation models for different strata; determine oil content based on the established resistivity interpretation model, and realize continuous characterization of oil content based on conventional logging curves. The present invention realizes continuous characterization of shale oil content based on conventional logging curves, filling the gap in this field.

Description

Technical Field

[0001] The present invention relates to the technical field of quantitative characterization of oil content of unconventional oil and gas, and in particular to a method for continuously characterizing the oil content distribution of mixed shale oil. Background Art

[0002] In recent years, the exploration and development of unconventional resources represented by shale oil and gas have become increasingly important. Mud shale layers in the oil window generally contain oil, but only shale layers with high oil abundance have development value. Accurate and continuous acquisition of shale oil content is critical for shale oil resource evaluation and sweet spot layer selection. Existing shale oil content continuous characterization technologies mainly include two categories: one is based on nuclear magnetic resonance logging, and the other is an evaluation technology based on ΔlgR logging.

[0003] Nuclear magnetic resonance logging technology is an important research method for calculating layer porosity and characterizing pore structure. The value of movable porosity can be obtained by nuclear magnetic resonance measurement before and after core centrifugation. Nuclear magnetic resonance logging can directly measure reservoir physical properties and free fluid seepage characteristics without being affected by lithology. It realizes continuous characterization of oil content based on laboratory calibration of oil-bearing cutoff aperture, but this technology has the disadvantages of high cost and long interpretation cycle. The evaluation technology based on ΔlgR logging is to calibrate the ΔlgR (acoustic-resistivity amplitude difference) model using laboratory measurement of residual hydrocarbons. This technology is mainly suitable for shale reservoirs with relatively stable mineral composition. Due to the complex lithology of mixed rocks, multiple mineral types, and strong oil heterogeneity, this technology is difficult to apply to mixed shale oil. At present, there is no reference method for continuous distribution characterization of oil content in mixed shale oil based on conventional logging curves.

[0004] The prior art has the following disadvantages:

[0005] 1. Nuclear magnetic logging technology is expensive and has a long interpretation cycle;

[0006] 2. The evaluation technology based on ΔlgR logging is mainly applicable to shale reservoirs with relatively stable mineral composition and is difficult to apply to mixed shale oil. Summary of the invention

[0007] In order to solve the problems existing in the prior art, the present invention provides a method for continuously characterizing the oil content distribution of mixed shale oil, comprising the following steps: step one, conducting core porosity and oil content tests on mixed rock samples of different lithologies; step two, selecting logging curves, and constructing mixed shale reservoir porosity interpretation models and clay interpretation models according to different lithologies; step three, carrying out rock electrical experiments on mixed rock samples of different lithologies in step one, constructing mixed shale reservoir porosity and clay interpretation models according to the constructed different lithologies based on the Archie conductive model, determining rock electrical parameters according to different lithologies, establishing rock electrical parameter interpretation models, and establishing saturation index interpretation models according to different lithologies; step four, inverting formation water resistivity values ​​according to the measured oil saturation data in step one and the rock electrical parameter interpretation model in step three, and establishing resistivity value interpretation models according to different strata; step five, determining the oil content according to the established resistivity interpretation model, and realizing continuous characterization of the oil content based on conventional logging curves. The present invention realizes continuous characterization of shale oil content based on conventional well logging curves.

[0008] The present invention provides a method for continuously characterizing the oil content distribution of mixed shale oil, comprising the following steps:

[0009] Step 1: Conduct core porosity and oil content tests on mixed rock samples of different lithologies;

[0010] Step 2: Select the well logging curve and construct the porosity interpretation model and clay interpretation model of the mixed shale reservoir according to different lithologies;

[0011] Step 3: Carry out rock electrical experiments on the mixed rock samples of different lithologies in step 1, and construct a porosity and clay interpretation model of mixed shale reservoir according to the Archie conductive model and the constructed different lithologies, determine rock electrical parameters for different lithologies, establish a rock electrical parameter interpretation model, and establish a saturation index interpretation model for different lithologies;

[0012] Step 4: Invert the formation water resistivity value based on the measured oil saturation data in step 1 and the rock electrical parameter interpretation model in step 3, and establish a resistivity value interpretation model for different layers;

[0013] Step five: determine the oil content based on the established resistivity interpretation model to achieve continuous characterization of the oil content based on conventional logging curves.

[0014] Preferably, step 1 is to conduct core porosity and oil content testing, specifically including oil content, water content, rock bulk density, porosity and clay content testing, to obtain the oil saturation of the sample.

[0015] Preferably, in step 1, during the core porosity and oil content test, the core depth is returned according to the correlation between the measured porosity and the three-porosity logging curve. The core depth is inaccurate due to various factors in coring, and the depth can be returned according to rock physics experimental methods or core and imaging matching methods. The present invention compares the measured porosity (core depth is known) with the logging porosity, and the three-porosity logging curve characteristics can reflect certain lithological characteristics, and the core depth is returned according to the above information comparison.

[0016] Preferably, in step 2, the well logging curve is selected based on the measured core porosity and the corresponding well logging curve.

[0017] Preferably, in step 2, by establishing a correlation chart of measured porosity and related curves, a curve with the best correlation between measured core porosity and corresponding logging curve is selected to construct a porosity interpretation model.

[0018] Preferably, in step 2, the measured core porosity is compared with the corresponding porosity curve, and the compensated density DEN curve with the best correlation is selected to construct four types of porosity interpretation models for siltstone, dolomite siltstone, dolomite and mudstone, respectively.

[0019] Preferably, in step 2, a clay content interpretation model is established according to the correlation between the limestone porosity difference, the neutron logging curve and the clay content.

[0020] Preferably, in step 2, a clay content interpretation model of siltstone and dolomitic siltstone is established by the difference between the neutron logging curve and the density porosity.

[0021] Preferably, the clay content interpretation model of siltstone and dolomitic siltstone is as shown in the following formula:

[0022] Vsh=26.699*ΔΦ+2.5486;

[0023] in,

[0024] Vsh is clay mineral content, %;

[0025] ΔΦ is the difference between the neutron logging curve and the density apparent porosity, %.

[0026] Preferably, a clay content interpretation model for mudstone and dolomite is established based on the neutron logging curve.

[0027] Preferably, the clay content interpretation model of mudstone and dolomite is as shown in the following formula:

[0028] Vsh = 0.5383*PHIN-7.4225;

[0029] in,

[0030] Vsh is clay mineral content, %;

[0031] PHIN is the value of neutron logging curve, %.

[0032] Preferably, in step three, rock electrical parameter interpretation and oil content calculation are performed based on the porosity interpretation model and the clay interpretation model.

[0033] Preferably, in step 3, using the relationship chart between porosity Φ and formation factor F, different lithologies are fitted to obtain lithology coefficient a and cementation index m;

[0034] Preferably, in step 3, using the relationship chart of porosity Φ and formation factor F, according to the following Archie formula, different lithologies are fitted to obtain lithology coefficient a and cementation index m;

[0035] F=a / Φ m ;

[0036] in,

[0037] F is the formation factor, dimensionless;

[0038] Φ is porosity, %;

[0039] a is the lithology coefficient, dimensionless;

[0040] m is the cementation index, dimensionless;

[0041] Preferably, the relationship between the resistivity increase rate and the water saturation Sw is used to obtain the lithology coefficient b and the saturation index n by fitting different lithologies;

[0042] Preferably, the relationship between the resistivity increase rate and the water saturation Sw is used to fit different lithologies to obtain the lithology coefficient b and the saturation index n according to the following Archie formula:

[0043] I=b / w n ;

[0044] in,

[0045] I is the resistivity increase index, dimensionless;

[0046] S w is water saturation, %;

[0047] b is the lithology coefficient, dimensionless;

[0048] n is the saturation index, dimensionless.

[0049] Preferably, the lithology coefficient a, lithology coefficient b and cementation index m of mixed rocks of the same lithology are fixed.

[0050] Preferably, the lithology coefficient b is obtained by taking the average value of the same lithology.

[0051] Preferably, an interpretation model of the saturation index n is established for different lithologies according to the relationship between the saturation index n and the porosity, clay content, burial depth and particle size.

[0052] Preferably, the interpretation models of saturation index n of micritic dolomite, dolomitic siltstone, feldspathic siltstone, argillaceous siltstone and shale are respectively as follows:

[0053] n=0.5224*ln(Vsh)+1.8983;

[0054]

[0055]

[0056] n=Max{1.3233*exp(0.1179*Vsh),(0.0008*DEPT-0.8265)};

[0057] n=Max{1.3233*exp(0.1179*Vsh),(0.0008*DEPT-0.8265)};

[0058] in,

[0059] n is the saturation index, dimensionless;

[0060] Vsh is the mud content, %;

[0061] Φ is porosity, %;

[0062] DEPT is the depth, m.

[0063] Preferably, in step 4, the inverted formation water resistivity value Rw is calculated using the following formula:

[0064] R w =R t Φ m S w n / (ab)

[0065] in,

[0066] R w is the formation water resistivity, Ω·m;

[0067] R t is the formation resistivity, Ω·m;

[0068] Φ is porosity, %;

[0069] S w is water saturation, %;

[0070] a and b are both lithology coefficients and are dimensionless;

[0071] m is the cementation index, dimensionless;

[0072] n is the saturation index, dimensionless.

[0073] Preferably, the oil content is determined using the following formula based on continuous well logging porosity, oil saturation interpretation model, crude oil density and rock density:

[0074] C=Φ1S o ρ o / ρ b ,

[0075] Φ1 is the continuous logging porosity;

[0076] S o is the oil saturation, %;

[0077] ρ o is the crude oil density, kg / m 3 ;

[0078] ρ b is the rock density, kg / m 3 ;

[0079] C is the oil content per unit rock, mg / g.

[0080] Based on the parameters required for oil saturation calculation: a, b, m, n, Rw, Φ and logging curve Rt, the oil saturation is calculated according to Archie's derivation formula:

[0081] S o =(abRw / RtΦ m )^(1 / n);

[0082] Crude oil density ρ o and rock density ρ b is a known value actually measured.

[0083] The oil content calculated here refers to the total oil content per unit rock, which can also be understood as the oil content rate. The exact value calculated is called the shale oil resource. The exact value can only be obtained by knowing the rock quality based on the oil content.

[0084] Compared with the prior art, the present invention has at least the following beneficial effects:

[0085] (1) The present invention only requires conventional logging curves to achieve continuous characterization of the oil content of mixed shale oil, and the interpretation accuracy can reach more than 80%. The interpretation cost and cycle are effectively reduced, which effectively supports the oil content evaluation of mixed shale reservoirs and the optimization of sweet spots. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] Figure 1 This is a flow chart of a method for continuously depicting the oil content distribution of mixed shale oil according to an embodiment of the present invention;

[0087] Figure 2a A schematic diagram of the relationship between porosity and compensation density DEN of dolomite according to an embodiment of the present invention;

[0088] Figure 2b A schematic diagram of the relationship between porosity and compensation density DEN of dolomitic siltstone according to an embodiment of the present invention;

[0089] Figure 2c A schematic diagram of the relationship between the porosity and the compensation density DEN of siltstone according to an embodiment of the present invention;

[0090] Figure 2d A schematic diagram of the relationship between the porosity and the compensation density DEN of mudstone according to an embodiment of the present invention;

[0091] Figure 3 A schematic diagram of the relationship between the inverted formation water resistivity and porosity according to an embodiment of the present invention;

[0092] Figure 4 This is a schematic diagram of the interpretation results of the oil content of mixed shale according to an embodiment of the present invention. DETAILED DESCRIPTION

[0093] The following is combined with Figure 1-4 , the specific implementation methods of the present invention are described in detail.

[0094] The present invention provides a method for continuously characterizing the oil content distribution of mixed shale oil, comprising the following steps:

[0095] Step 1: Conduct core porosity and oil content tests on mixed rock samples of different lithologies;

[0096] Step 2: Select the well logging curve and construct the porosity interpretation model and clay interpretation model of the mixed shale reservoir according to different lithologies;

[0097] Step 3: Carry out rock electrical experiments on the mixed rock samples of different lithologies in step 1, and construct a porosity and clay interpretation model of mixed shale reservoir according to the Archie conductive model and the constructed different lithologies, determine rock electrical parameters for different lithologies, establish a rock electrical parameter interpretation model, and establish a saturation index interpretation model for different lithologies;

[0098] Step 4: Invert the formation water resistivity value based on the measured oil saturation data in step 1 and the rock electrical parameter interpretation model in step 3, and establish a resistivity value interpretation model for different layers;

[0099] Step five: determine the oil content based on the established resistivity interpretation model to achieve continuous characterization of the oil content based on conventional logging curves.

[0100] As a preferred implementation, step 1 is to conduct core porosity and oil content testing, specifically including oil content, water content, rock bulk density, porosity and clay content testing, to obtain the oil saturation of the sample.

[0101] As a preferred implementation, in step 1, during the core porosity and oil content test, core depth retrieval is performed based on the correlation between the measured porosity and the three-porosity logging curves.

[0102] As a preferred implementation, in step 2, the well logging curve is selected based on the measured core porosity and the corresponding well logging curve.

[0103] As a preferred implementation, in step 2, by establishing a correlation chart between the measured porosity and the relevant curves, a curve with the best correlation between the measured core porosity and the corresponding logging curve is selected to construct a porosity interpretation model.

[0104] As a preferred implementation, in step 2, the measured core porosity is compared with the corresponding porosity curve, and the compensated density DEN curve with the best correlation is selected to construct four types of porosity interpretation models for siltstone, dolomitic siltstone, dolomite and mudstone, respectively.

[0105] As a preferred implementation, in step 2, a clay content interpretation model is established based on the correlation between limestone porosity difference, neutron logging curve and clay content.

[0106] As a preferred implementation, in step 2, a clay content interpretation model of siltstone and dolomitic siltstone is established by using the difference between the neutron logging curve and the density porosity.

[0107] As a preferred embodiment, the clay content interpretation model of siltstone and dolomitic siltstone is shown in the following formula:

[0108] Vsh=26.699*ΔΦ+2.5486;

[0109] in,

[0110] Vsh is clay mineral content, %;

[0111] ΔΦ is the difference between the neutron logging curve and the density apparent porosity, %.

[0112] As a preferred implementation, a clay content interpretation model for mudstone and dolomite is established based on neutron logging curves.

[0113] As a preferred embodiment, the clay content interpretation model of mudstone and dolomite is shown in the following formula:

[0114] Vsh = 0.5383*PHIN-7.4225;

[0115] in,

[0116] Vsh is clay mineral content, %;

[0117] PHIN is the value of neutron logging curve, %.

[0118] As a preferred implementation, in step three, rock electrical parameter interpretation and oil content calculation are performed based on the porosity interpretation model and the clay interpretation model.

[0119] As a preferred implementation, in step 3, using the relationship chart between porosity Φ and formation factor F, different lithologies are fitted to obtain lithology coefficient a and cementation index m;

[0120] As a preferred implementation, in step 3, using the relationship chart of porosity Φ and formation factor F, according to the following Archie formula, different lithologies are fitted to obtain lithology coefficient a and cementation index m;

[0121] F=a / Φ m ;

[0122] in,

[0123] F is the formation factor, dimensionless;

[0124] Φ is porosity, %;

[0125] a is the lithology coefficient, dimensionless;

[0126] m is the cementation index, dimensionless;

[0127] As a preferred implementation, the relationship between the resistivity increase rate and the water saturation Sw is used to obtain the lithology coefficient b and the saturation index n according to different lithologies;

[0128] As a preferred implementation, the relationship between the resistivity increase rate and the water saturation Sw is used to obtain the lithology coefficient b and the saturation index n by fitting different lithologies according to the following Archie formula:

[0129] I=b / w n ;

[0130] in,

[0131] I is the resistivity increase index, dimensionless;

[0132] S w is water saturation, %;

[0133] b is the lithology coefficient, dimensionless;

[0134] n is the saturation index, dimensionless.

[0135] As a preferred embodiment, the lithology coefficient a, lithology coefficient b and cementation index m of mixed rocks of the same lithology are fixed.

[0136] As a preferred implementation, the lithology coefficient b is obtained by taking the average value of the same lithology.

[0137] As a preferred implementation, according to the relationship between the saturation index n and porosity, clay content, burial depth and particle size, an interpretation model of the saturation index n is established for different lithologies. The interpretation models of the saturation index n of micrite dolomite, dolomitic siltstone, feldspathic siltstone, argillaceous siltstone and shale are as follows:

[0138] n=0.5224*ln(Vsh)+1.8983;

[0139]

[0140]

[0141] n=Max{1.3233*exp(0.1179*Vsh),(0.0008*DEPT-0.8265)};

[0142] n=Max{1.3233*exp(0.1179*Vsh),(0.0008*DEPT-0.8265)};

[0143] in,

[0144] n is the saturation index, dimensionless;

[0145] Vsh is the mud content, %;

[0146] Φ is porosity, %;

[0147] DEPT is the depth, m.

[0148] As a preferred implementation, in step 4, the inverted formation water resistivity value Rw is calculated using the following formula:

[0149] R w =R t Φ m S w n / (ab)

[0150] in,

[0151] R w is the formation water resistivity, Ω·m;

[0152] R t is the formation resistivity, Ω·m;

[0153] Φ is porosity, %;

[0154] S w is water saturation, %;

[0155] a and b are both lithology coefficients and are dimensionless;

[0156] m is the cementation index, dimensionless;

[0157] n is the saturation index, dimensionless.

[0158] As a preferred embodiment, the oil content is determined by the following formula based on continuous logging porosity, oil saturation interpretation model, crude oil density and rock density:

[0159] C=Φ1S o ρ o / ρ b ,

[0160] Φ1 is the continuous logging porosity;

[0161] S o is the oil saturation, %;

[0162] ρ o is the crude oil density, kg / m 3 ;

[0163] ρ b is the rock density, kg / m 3 ;

[0164] C is the oil content per unit rock, mg / g.

[0165] Example 1

[0166] According to a specific embodiment of the present invention, the method of the present invention for continuously characterizing the oil content distribution of mixed shale oil is described in detail below.

[0167] The present invention provides a method for continuously characterizing the oil content distribution of mixed shale oil, comprising the following steps:

[0168] Step 1: Conduct core porosity and oil content tests on mixed rock samples of different lithologies;

[0169] Step 2: Select the well logging curve and construct the porosity interpretation model and clay interpretation model of the mixed shale reservoir according to different lithologies;

[0170] Step 3: Carry out rock electrical experiments on the mixed rock samples of different lithologies in step 1, and construct a porosity and clay interpretation model of mixed shale reservoir according to the Archie conductive model and the constructed different lithologies, determine rock electrical parameters for different lithologies, establish a rock electrical parameter interpretation model, and establish a saturation index interpretation model for different lithologies;

[0171] Step 4: Invert the formation water resistivity value based on the measured oil saturation data in step 1 and the rock electrical parameter interpretation model in step 3, and establish a resistivity value interpretation model for different layers;

[0172] Step five: determine the oil content based on the established resistivity interpretation model to achieve continuous characterization of the oil content based on conventional logging curves.

[0173] Example 2

[0174] According to a specific embodiment of the present invention, the method of the present invention for continuously characterizing the oil content distribution of mixed shale oil is described in detail below.

[0175] The present invention provides a method for continuously characterizing the oil content distribution of mixed shale oil, comprising the following steps:

[0176] Step 1: Conduct core porosity and oil content tests on mixed rock samples of different lithologies; Step 1: Conduct core porosity and oil content tests specifically including oil content, water content, rock volume density, porosity and clay content tests to obtain the oil saturation of the sample; Step 1: During the core porosity and oil content test, core depth homing is performed based on the correlation between the measured porosity and the three-porosity logging curves;

[0177] Step 2: By establishing a correlation chart between the measured porosity and the relevant curve, the curve with the best correlation between the measured core porosity and the corresponding logging curve is selected to construct a porosity interpretation model; in step 2, a clay content interpretation model is established based on the correlation between the limestone porosity difference, the neutron logging curve and the clay content.

[0178] Step 3: Carry out rock electrical experiments on the mixed rock samples of different lithologies in step 1, and construct porosity and clay interpretation models of mixed shale reservoirs according to the Archie conductive model and the constructed different lithologies, determine rock electrical parameters for different lithologies, establish rock electrical parameter interpretation models, and establish saturation index interpretation models for different lithologies; In step 3, perform rock electrical parameter interpretation and oil content calculation according to the porosity interpretation model and the clay interpretation model;

[0179] Step 4: Invert the formation water resistivity value based on the measured oil saturation data in step 1 and the rock electrical parameter interpretation model in step 3, and establish a resistivity value interpretation model for different layers;

[0180] Step five: determine the oil content based on the established resistivity interpretation model to achieve continuous characterization of the oil content based on conventional logging curves.

[0181] Example 3

[0182] According to a specific embodiment of the present invention, the method of the present invention for continuously characterizing the oil content distribution of mixed shale oil is described in detail below.

[0183] The present invention provides a method for continuously characterizing the oil content distribution of mixed shale oil, comprising the following steps:

[0184] Step 1: Conduct core porosity and oil content tests on mixed rock samples of different lithologies; Step 1: Conduct core porosity and oil content tests specifically including oil content, water content, rock volume density, porosity and clay content tests to obtain the oil saturation of the sample; Step 1: During the core porosity and oil content test, core depth homing is performed based on the correlation between the measured porosity and the three-porosity logging curves;

[0185] Step 2: By establishing a correlation chart between the measured porosity and the relevant curves, the curve with the best correlation between the measured core porosity and the corresponding logging curve is selected to construct a porosity interpretation model;

[0186] in,

[0187] A clay content interpretation model was established based on the correlation between limestone porosity difference, neutron logging curve and clay content;

[0188] By comparing the correlation between the measured core porosity and the corresponding porosity curve, the compensated density DEN curve with the best correlation was selected, and four porosity interpretation models of siltstone, dolomitic siltstone, dolomite and mudstone were constructed respectively.

[0189] The clay content interpretation model of siltstone and dolomite siltstone is established by the difference between the neutron logging curve and the density porosity; the clay content interpretation model of siltstone and dolomite siltstone is shown in the following formula:

[0190] Vsh=26.699*ΔΦ+2.5486;

[0191] in,

[0192] Vsh is clay mineral content, %;

[0193] ΔΦ is the difference between the neutron logging curve and the density apparent porosity, %.

[0194] The clay content interpretation model of mudstone and dolomite is established based on the neutron logging curve; the clay content interpretation model of mudstone and dolomite is shown in the following formula:

[0195] Vsh = 0.5383*PHIN-7.4225;

[0196] in,

[0197] Vsh is clay mineral content, %;

[0198] PHIN is the value of neutron logging curve, %.

[0199] Step 3: Carry out rock electrical experiments on the mixed rock samples of different lithologies in step 1, and construct a porosity and clay interpretation model of mixed shale reservoir according to the Archie conductive model and the constructed different lithologies, determine rock electrical parameters for different lithologies, establish a rock electrical parameter interpretation model, and establish a saturation index interpretation model for different lithologies;

[0200] in,

[0201] Interpret rock electrical parameters and calculate oil content based on porosity interpretation model and clay interpretation model;

[0202] Using the relationship chart between porosity Φ and formation factor F, the lithology coefficient a and cementation index m are obtained by fitting different lithologies; using the relationship between resistivity increase rate and water saturation Sw, the lithology coefficient b and saturation index n are obtained by fitting different lithologies;

[0203] According to the relationship between saturation index n and porosity, clay content, burial depth and grain size, the interpretation model of saturation index n is established for different lithologies.

[0204] Step 4: Invert the formation water resistivity value based on the measured oil saturation data in step 1 and the rock electrical parameter interpretation model in step 3, and establish a resistivity value interpretation model for different layers;

[0205] Among them, the inverted formation water resistivity value Rw is calculated using the following formula:

[0206] R w =R t Φ m S w n / (ab)

[0207] in,

[0208] R w is the formation water resistivity, Ω·m;

[0209] R t is the formation resistivity, Ω·m;

[0210] Φ is porosity, %;

[0211] S w is water saturation, %;

[0212] a and b are both lithology coefficients and are dimensionless;

[0213] m is the cementation index, dimensionless;

[0214] n is the saturation index, dimensionless.

[0215] Step 5: Determine the oil content based on the established resistivity interpretation model to achieve continuous characterization of the oil content based on conventional logging curves;

[0216] Among them, the oil content is determined by the following formula based on continuous logging porosity, oil saturation interpretation model, crude oil density and rock density:

[0217] C=Φ1S o ρ o / ρ b ,

[0218] Φ1 is the continuous logging porosity;

[0219] S o is the oil saturation, %;

[0220] ρ o is the crude oil density, kg / m 3 ;

[0221] ρ b is the rock density, kg / m 3 ;

[0222] C is the oil content per unit rock, mg / g.

[0223] Example 4

[0224] According to a specific embodiment of the present invention, the method of the present invention for continuously characterizing the oil content distribution of mixed shale oil is described in detail below.

[0225] The present invention provides a method for continuously characterizing the oil content distribution of mixed shale oil, comprising the following steps:

[0226] Step 1: Conduct core porosity and oil content tests on mixed rock samples of different lithologies; Step 1: Conduct core porosity and oil content tests specifically including oil content, water content, rock volume density, porosity and clay content tests to obtain the oil saturation of the sample; Step 1: During the core porosity and oil content test, core depth homing is performed based on the correlation between the measured porosity and the three-porosity logging curves;

[0227] Step 2: By establishing a correlation chart between the measured porosity and the relevant curves, the curve with the best correlation between the measured core porosity and the corresponding logging curve is selected to construct a porosity interpretation model;

[0228] in,

[0229] A clay content interpretation model was established based on the correlation between limestone porosity difference, neutron logging curve and clay content;

[0230] By comparing the correlation between the measured core porosity and the corresponding porosity curve, the compensated density DEN curve with the best correlation was selected, and four porosity interpretation models of siltstone, dolomitic siltstone, dolomite and mudstone were constructed respectively.

[0231] The clay content interpretation model of siltstone and dolomite siltstone is established by the difference between the neutron logging curve and the density porosity; the clay content interpretation model of siltstone and dolomite siltstone is shown in the following formula:

[0232] Vsh=26.699*ΔΦ+2.5486;

[0233] in,

[0234] Vsh is clay mineral content, %;

[0235] ΔΦ is the difference between the neutron logging curve and the density apparent porosity, %.

[0236] The clay content interpretation model of mudstone and dolomite is established based on the neutron logging curve; the clay content interpretation model of mudstone and dolomite is shown in the following formula:

[0237] Vsh = 0.5383*PHIN-7.4225;

[0238] in,

[0239] Vsh is clay mineral content, %;

[0240] PHIN is the value of neutron logging curve, %.

[0241] Step 3: Carry out rock electrical experiments on the mixed rock samples of different lithologies in step 1, and construct a porosity and clay interpretation model of mixed shale reservoir according to the Archie conductive model and the constructed different lithologies, determine rock electrical parameters for different lithologies, establish a rock electrical parameter interpretation model, and establish a saturation index interpretation model for different lithologies;

[0242] in,

[0243] Interpret rock electrical parameters and calculate oil content based on porosity interpretation model and clay interpretation model;

[0244] Using the relationship chart between porosity Φ and formation factor F, according to the following Archie formula, the lithology coefficient a and cementation index m are obtained by fitting different lithologies;

[0245] F=a / Φ m ;

[0246] in,

[0247] F is the formation factor, dimensionless;

[0248] Φ is porosity, %;

[0249] a is the lithology coefficient, dimensionless;

[0250] m is the cementation index, dimensionless; according to the relationship between the saturation index n and porosity, clay content, burial depth and grain size, the interpretation model of the saturation index n is established for different lithologies;

[0251] Using the relationship between the resistivity increase rate and the water saturation Sw, according to the following Archie formula, the lithology coefficient b and saturation index n are obtained by fitting different lithologies:

[0252] I=b / S w n ;

[0253] in,

[0254] I is the resistivity increase index, dimensionless;

[0255] S w is water saturation, %;

[0256] b is the lithology coefficient, dimensionless;

[0257] n is the saturation index, dimensionless.

[0258] The lithology coefficient a, lithology coefficient b and cementation index m of mixed rocks with the same lithology are fixed; the lithology coefficient b is obtained by taking the average value for the same lithology.

[0259] Among them, the interpretation models of saturation index n of micritic dolomite, dolomitic siltstone, feldspathic siltstone, argillaceous siltstone and shale are as follows:

[0260] n=0.5224*ln(Vsh)+1.8983;

[0261]

[0262]

[0263] n=Max{1.3233*exp(0.1179*Vsh),(0.0008*DEPT-0.8265)};

[0264] n=Max{1.3233*exp(0.1179*Vsh),(0.0008*DEPT-0.8265)};

[0265] in,

[0266] n is the saturation index, dimensionless;

[0267] Vsh is the mud content, %;

[0268] Φ is porosity, %;

[0269] DEPT is the depth, m.

[0270] Step 4: Invert the formation water resistivity value based on the measured oil saturation data in step 1 and the rock electrical parameter interpretation model in step 3, and establish a resistivity value interpretation model for different layers;

[0271] Among them, the inverted formation water resistivity value Rw is calculated using the following formula:

[0272] R w =R t Φ m S w n / (ab)

[0273] in,

[0274] R w is the formation water resistivity, Ω·m;

[0275] R t is the formation resistivity, Ω·m;

[0276] Φ is porosity, %;

[0277] S w is water saturation, %;

[0278] a and b are both lithology coefficients and are dimensionless;

[0279] m is the cementation index, dimensionless;

[0280] n is the saturation index, dimensionless.

[0281] Step 5: Determine the oil content based on the established resistivity interpretation model to achieve continuous characterization of the oil content based on conventional logging curves;

[0282] Among them, the oil content is determined by the following formula based on continuous logging porosity, oil saturation interpretation model, crude oil density and rock density:

[0283] C=Φ1S o ρo / ρ b ,

[0284] Φ1 is the continuous logging porosity;

[0285] S o is the oil saturation, %;

[0286] ρ o is the crude oil density, kg / m 3 ;

[0287] ρ b is the rock density, kg / m 3 ;

[0288] C is the oil content per unit rock, mg / g.

[0289] Example 5

[0290] According to a specific embodiment of the present invention, the method of the present invention for continuously characterizing the oil content distribution of mixed shale oil is described in detail below.

[0291] The present invention provides a method for continuously characterizing the oil content distribution of mixed shale oil, comprising the following steps:

[0292] 1) Conduct core porosity and oil content testing:

[0293] Fresh core samples are preferred, preferably sealed core samples, and oil content, water content, rock bulk density, porosity and clay content tests are performed to obtain oil saturation data of fresh samples.

[0294] Among them, the porosity is based on GB / T 34533-2017 "Determination of shale porosity and permeability", the oil content and water content are based on SY-T 6369-1998 "Core oil and water saturation tester", and the clay content is based on SY-T 5163-2010 "X-ray diffraction analysis method for clay minerals and common non-clay minerals in sedimentary rocks";

[0295] According to the correlation between the measured porosity and the three-porosity logging curve, the core depth is returned. The test data can cover the main rock types of mixed shale reservoirs, and each rock type has no less than 10 data points.

[0296] 2) Optimize logging curves to construct porosity and clay interpretation models for mixed shale reservoirs:

[0297] Based on the measured core porosity and the corresponding logging curve value, the best correlation curve between the two is selected to construct the porosity model. By comparison, the compensation density curve DEN is selected, and the porosity interpretation models are constructed for four categories: siltstone, dolomitic siltstone, dolomite and mudstone, and the interpretation accuracy is above 70%. In this embodiment, the relationship between the porosity of different lithologies and the compensation density DEN is shown in Figure 2.

[0298] A clay evaluation model was established based on the correlation between the porosity difference of limestone, the neutron curve and the clay content. A clay content model was established for siltstone and dolomite siltstone through the neutron-density porosity difference, Vsh=26.699*ΔΦ+2.5486 (Vsh is the clay mineral content, %; ΔΦ is the neutron-density apparent porosity difference, %); a clay content interpretation model was established for mudstone and dolomite through the neutron logging curve: Vsh=0.5383*PHIN-7.4225 (Vsh is the clay mineral content, %; PHIN is the neutron curve value, %).

[0299] The porosity and clay interpretation models provide basic parameters for subsequent rock electrical parameter interpretation and oil content calculation.

[0300] 3) Optimize the mixed rock samples of different lithologies in step 1), carry out rock electrical experiments according to the centrifuge method steps in SY / T 5385-2007 "Laboratory Measurement and Calculation Methods of Rock Resistivity Parameters", and determine the conductive parameters according to the Archie conductive model:

[0301] Using the porosity Φ-formation factor F relationship chart, the lithology coefficient a and cementation index m are obtained by lithology fitting. Using the relationship between resistivity increase rate and water saturation Sw, b and saturation index n of each sample are fitted.

[0302] On this basis, the average value of the same lithology is taken to obtain b, and the interpretation model of n is established for each lithology according to the relationship between n and porosity, clay content, burial depth, particle size, etc. The n value of dolomite siltstone is affected by porosity and clay. When the clay content is low, the saturation index n tends to 2 with the increase of porosity. As the clay content increases, the n value increases rapidly. The n value of mud crystal dolomite is also affected by clay, but the n value of siltstone is less affected by clay. The n value of siltstone is affected by burial depth, clay content and particle size. The greater the burial depth, the greater the n value, the finer the particle size, and the greater the influence of clay on the saturation index n. The rock electrical parameters of different lithologies obtained in this embodiment are shown in Table 1.

[0303] Table 1 Examples of rock electrical parameters for different lithologies

[0304]

[0305] According to the relationship between formation water resistivity Rw in Archie model: R w =R t Φm S w n / (ab)(R w is the formation water resistivity, Ω·m; Rt is the formation resistivity, Ω·m; Φ is the porosity, %; S w is water saturation, %), combined with the above-mentioned rock electrical parameters, true formation resistivity Rt, core porosity Φ and measured water saturation Sw and other data, the Rw value of each sampled electrode is calculated. The schematic diagram of the relationship between inversion of formation water resistivity and porosity is shown in Figure 3 .

[0306] According to the relationship between Rw, porosity and lithology, the formation water resistivity interpretation model is established in different layers. The overall formation water resistivity ranges from 0.005 to 0.1Ω·m, and increases exponentially with the porosity. The upper sweet spot Rw = 0.001Φ 1.2621 , lower sweet spot Rw=0.0011Φ 1.1035 .

[0307] According to the above porosity Φ, oil saturation S o Explanation model, combined with crude oil density ρ o and rock bulk density curve ρ b And other data, calculate the oil content C = ΦS o ρ o / ρ b , and then realize the continuous characterization of oil content based on conventional logging curves. The interpretation results of oil content of mixed shale are shown in Figure 4 .

[0308] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.

Claims

1. A method for continuously characterizing the oil content distribution of mixed shale oil, characterized in that: The steps include: Step 1: Conduct core porosity and oil content tests on mixed rock samples of different lithologies; Step 2: Select the well logging curve and construct the porosity interpretation model and clay interpretation model of the mixed shale reservoir according to different lithologies; Step 3: Carry out rock electrical experiments on the mixed rock samples of different lithologies in step 1, and construct a porosity and clay interpretation model of mixed shale reservoir according to the Archie conductive model and the constructed different lithologies, determine rock electrical parameters for different lithologies, establish a rock electrical parameter interpretation model, and establish a saturation index interpretation model for different lithologies; Step 4: Invert the formation water resistivity value based on the measured oil saturation data in step 1 and the rock electrical parameter interpretation model in step 3, and establish a resistivity value interpretation model for different layers; Step 5: Determine the oil content based on the established resistivity interpretation model to achieve continuous characterization of the oil content based on conventional logging curves; In step 4, the inverted formation water resistivity value Rw is calculated using the following formula: R w =R t Φ m S w n / (ab) in, R w is the formation water resistivity, Ω·m; R t is the formation resistivity, Ω·m; Φ is porosity, %; S w is water saturation, %; a and b are lithology coefficients; m is the cementation index; n is the saturation index; In step 5, the oil content is determined using the following formula based on the continuous logging porosity, oil saturation interpretation model, crude oil density and rock density: C=Φ1S o r o / r b , Φ1 is the continuous logging porosity; S o is the oil saturation, %; ρ o is the crude oil density, kg / m 3 ; ρ b is the rock density, kg / m 3 ; C is the oil content per unit rock, mg / g.

2. The method for continuously characterizing the oil content distribution of mixed shale oil according to claim 1, characterized in that: Step 1: Conduct core porosity and oil content tests, including oil content, water content, rock bulk density, porosity and clay content tests, to obtain the oil saturation of the sample.

3. The method for continuously characterizing the oil content distribution of mixed shale oil according to claim 2, characterized in that: Step 1 During the core porosity and oil content test, the core depth is returned based on the correlation between the measured porosity and the three-porosity logging curves.

4. The method for continuously characterizing the oil content distribution of mixed shale oil according to claim 3, characterized in that: In step 2, the logging curve is selected based on the measured core porosity and the corresponding logging curve.

5. The method for continuously characterizing the oil content distribution of mixed shale oil according to claim 4, characterized in that: In step 2, by establishing a correlation chart between the measured porosity and the relevant curves, the curve with the best correlation between the measured core porosity and the corresponding logging curve is selected to construct the porosity interpretation model.

6. The method for continuously characterizing the oil content distribution of mixed shale oil according to claim 5, characterized in that: In step 2, the correlation between the measured core porosity and the corresponding porosity curve is compared, and the compensated density DEN curve with the best correlation is selected to construct four types of porosity interpretation models for siltstone, dolomitic siltstone, dolomite and mudstone.

7. The method for continuously characterizing the oil content distribution of mixed shale oil according to claim 4, characterized in that: In step 2, a clay content interpretation model is established based on the correlation between limestone porosity difference, neutron logging curve and clay content.

8. The method for continuously characterizing the oil content distribution of mixed shale oil according to claim 7, characterized in that: In step 2, the clay content interpretation model of siltstone and dolomitic siltstone is established by the difference between the neutron logging curve and the density porosity.

9. The method for continuously characterizing the oil content distribution of mixed shale oil according to claim 8, characterized in that: The clay content interpretation model of siltstone and dolomitic siltstone is shown in the following formula: Vsh=26.699*ΔΦ+2.5486; in, Vsh is clay mineral content, %; ΔΦ is the difference between the neutron logging curve and the density apparent porosity, %.

10. The method for continuously characterizing the oil content distribution of mixed shale oil according to claim 6, characterized in that: The clay content interpretation model of mudstone and dolomite is established based on the neutron logging curve.

11. The method for continuously characterizing the oil content distribution of mixed shale oil according to claim 10, characterized in that: The clay content interpretation model of mudstone and dolomite is shown in the following formula: Vsh = 0.5383*PHIN-7.4225; in, Vsh is clay mineral content, %; PHIN is the value of neutron logging curve, %.

12. The method for continuously characterizing the oil content distribution of mixed shale oil according to any one of claims 1 to 11, characterized in that: In step three, the rock electrical parameters are interpreted and the oil content is calculated based on the porosity interpretation model and the clay interpretation model.

13. The method for continuously characterizing the oil content distribution of mixed shale oil according to claim 12, characterized in that: In step three, using the relationship chart between porosity Φ and formation factor F, different lithologies are fitted to obtain lithology coefficient a and cementation index m; using the relationship between resistivity increase rate and water saturation Sw, different lithologies are fitted to obtain lithology coefficient b and saturation index n.

14. The method for continuously characterizing the oil content distribution of mixed shale oil according to claim 13, characterized in that: The lithology coefficient a, lithology coefficient b and cementation index m of mixed rocks with the same lithology are taken as fixed values.

15. The method for continuously characterizing the oil content distribution of mixed shale oil according to claim 14, characterized in that: The lithology coefficient b is obtained by taking the average value of the same lithology.

16. The method for continuously characterizing the oil content distribution of mixed shale oil according to claim 13, characterized in that: According to the relationship between saturation index n and porosity, clay content, burial depth and grain size, an interpretation model of saturation index n is established for different lithologies.

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