A logging method and system for quantitative calculation of three-dimensional characterization of resistivity of thin interbeds

Abstract

The present invention provides a logging method and system for three-dimensional characterization and quantitative calculation of thin interbed resistivity, which solves the limitations of existing resistivity water saturation calculation technologies, improves the accuracy of logging water saturation calculation for complex thin interbed reservoirs, and further realizes accurate evaluation of oil-bearing properties of thin interbed reservoirs and calculation of oil and gas reserves. The method includes the following steps: collecting logging parameters of the target layer to be detected and performing preprocessing; establishing a thin interbed model based on logging data, and dividing the thin interbed model into four types according to anisotropic characteristics, including isotropic shale-sandstone model, anisotropic shale-sandstone model, isotropic shale-calcareous sandstone model, and anisotropic shale-calcareous sandstone model; selecting a corresponding type of model in the thin interbed model as the calculation model according to the preprocessed logging parameters; inputting the preprocessed logging parameters into the calculation model, calculating and outputting the thin interbed characterization parameters of the target layer to be detected, and completing the three-dimensional characterization and quantitative calculation logging.

Description

Technical Field

[0001] The present invention relates to the technical field of oil exploration logging, and specifically provides a logging method and system for quantitative calculation of three-dimensional characterization of thin interbed resistivity. Background Art

[0002] Thin interbed formations are an important oil and gas reservoir space. These formations exhibit typical resistivity anisotropy, mainly caused by the alternating deposition of mudstone with relatively low resistivity, sandstone with relatively high resistivity, and calcareous layers with even higher resistivity. Electrically anisotropic formations in logging are usually mainly composed of thin interbed formations of sandstone and mudstone thin layers smaller than the resolution of logging instruments. When the lithology and fluid properties of the oil and gas layer simultaneously affect the reservoir electrical properties, the absolute value of the actually measured resistivity cannot correctly reflect the reservoir fluid properties. Especially when there are low-resistivity mudstone and high-resistivity calcareous sandstone interferences in the area, relying on the resistivity value to judge the fluid properties in the sandstone reservoir often leads to opposite conclusions. Using it to calculate the oil and gas saturation of the formation will result in misjudgment, thus causing the result of missing oil and gas-bearing reservoirs.

[0003] Existing instruments currently available cannot meet the accurate measurement requirements of the above-mentioned thin interbed reservoirs in terms of resolution, nor can they characterize the anisotropic characteristics of the reservoir, which easily leads to inaccurate water saturation values of the calculated thin interbed anisotropic reservoirs. Summary of the Invention

[0004] To solve the problems existing in the prior art, the present invention provides a logging method and system for quantitative calculation of three-dimensional characterization of thin interbed resistivity, which solves the limitations of the existing resistivity water saturation calculation technology, improves the accuracy of calculating the water saturation of complex thin interbed reservoirs during logging, and further realizes accurate evaluation of the oil-bearing property of thin interbed reservoirs and calculation of oil and gas reserves.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A logging method for quantitative calculation of three-dimensional characterization of thin interbed resistivity includes the following steps:

[0007] Collect logging parameters of the target layer to be detected and perform preprocessing;

[0008] Establish a thin interbed model based on logging data. The thin interbed model is divided into four types of models according to anisotropic characteristics, including isotropic mudstone-sandstone model, anisotropic mudstone-sandstone model, isotropic mudstone-calcareous sandstone model, and anisotropic mudstone-calcareous sandstone model;

[0009] Select a corresponding type of model in the thin interbed model as the calculation model according to the preprocessed logging parameters;

[0010] Input the preprocessed logging parameters into the calculation model, calculate and output the thin interbed characterization parameters of the target layer to be detected, and complete the quantitative calculation of the three-dimensional characterization logging.

[0011] Preferably, the logging parameters of the target layer to be detected collected include three-dimensional induction resistivity curve, natural gamma curve GR, natural gamma energy spectrum U, and at least one porosity logging curve.

[0012] Preferably, the three-dimensional induction resistivity curve includes three-dimensional induction horizontal resistivity curve Rh and three-dimensional induction vertical resistivity curve Rv;

[0013] The porosity logging curve includes density curve DEN, compensated neutron curve CNL, and high-resolution acoustic curve HAC.

[0014] Preferably, the preprocessing of the logging parameters of the target layer to be detected includes,

[0015] Calculate the shale volume of the target layer to be detected according to the natural gamma curve or natural gamma energy spectrum U;

[0016] Calculate the calcareous layer volume content and porosity of the target layer to be detected according to the porosity logging curve;

[0017] Calculate the anisotropy coefficient of the target layer to be detected according to the three-dimensional induction resistivity curve.

[0018] Preferably, the expression of the isotropic shale-sandstone model includes the expression of sandstone resistivity and the expression of shale resistivity:

[0019] The expression of sandstone resistivity is,

[0020]

[0021] The expression of shale resistivity is,

[0022]

[0023] In the formula, R shale 、R sand 、V sand 、V shale are the shale resistivity, sandstone resistivity, sandstone volume, and shale volume of the target layer to be detected respectively. Among them, V sand +V shale =1, V shale is calculated according to the natural gamma curve or natural gamma energy spectrum U; R h 、R v respectively represent the horizontal resistivity and vertical resistivity measured by the three-dimensional induction instrument.

[0024] Preferably, the anisotropic mudstone-sandstone model expression includes the expression of sandstone resistivity and the expression of mudstone resistivity:

[0025] The expression of sandstone resistivity is

[0026]

[0027] The expression of mudstone resistivity is

[0028]

[0029] Wherein;

[0030] In the formula, R shale , R sand , V sand , V shale are respectively the mudstone resistivity, sandstone resistivity, sandstone volume and mudstone volume of the target layer to be detected, V sand +V shale = 1, V shale is obtained by calculating according to the natural gamma curve or natural gamma energy spectrum U; R h , R v respectively represent the horizontal resistivity and vertical resistivity measured by a three-dimensional induction instrument; R shale-h , R shale-v respectively represent the horizontal resistivity of the mudstone of the target layer to be detected and the vertical resistivity of the mudstone of the target layer to be detected obtained according to the logging data of the mudstone section.

[0031] Preferably, the expression of the isotropic mudstone-calcareous sandstone model includes:

[0032] V sand +V shale +V ca = 1;

[0033]

[0034] R v = R shale V shale +R sand V sand +R ca V ca ;

[0035] In the formula, R shale , R sand , V shale , V sand , R ca , V caare the resistivity of mudstone, resistivity of sandstone, volume of mudstone, volume of sandstone, resistivity of calcareous layer, and volume of mudstone in calcareous layer of the target layer to be detected, respectively, V shale is obtained by calculating according to the natural gamma curve or natural gamma energy spectrum U; R shale is obtained according to the logging data of the mudstone section; R h and R v respectively represent the horizontal resistivity and vertical resistivity measured by a three-dimensional induction instrument;

[0036] The resistivity of the calcareous layer R ca and the volume of mudstone in the calcareous layer V ca Convert the measured Rh and Rv to obtain the horizontal resistivity R h ' and vertical resistivity R v ' in the isotropic mudstone-calcareous sandstone model, and their expressions are respectively:

[0037]

[0038]

[0039] Preferably, the expression of the anisotropic mudstone-calcareous sandstone model includes:

[0040] V sand +V shale +V ca = 1;

[0041]

[0042] R v -R ca V ca = R shale-v V shale +R sand V sand ;

[0043] In the formula, R shale 、R sand 、V shale 、V sand 、R ca 、V ca are the resistivity of mudstone, resistivity of sandstone, volume of mudstone, volume of sandstone, resistivity of calcareous layer, and volume of mudstone in calcareous layer of the target layer to be detected, respectively, V shale and V ca are obtained by calculating according to the natural gamma curve or natural gamma energy spectrum U; R h 、R v respectively represent the horizontal resistivity and vertical resistivity measured by a three-dimensional induction instrument; R shale-h 、R shale-vrespectively represent the horizontal resistivity of the mudstone in the target layer to be detected and the vertical resistivity of the mudstone in the target layer to be detected obtained from the logging data of the mudstone section;

[0044] The resistivity R of the calcareous layer calculated according to the above formula ca and the mudstone volume V of the calcareous layer ca For the measured R h 、R v are transformed to obtain the horizontal resistivity R” h and the vertical resistivity R” v in the anisotropic mudstone-calcareous sandstone model, and their expressions are respectively:

[0045]

[0046]

[0047] Preferably, inputting the preprocessed logging parameters into the calculation model, the thin interbed characterization parameters of the target layer to be detected calculated and output include calculating the water saturation of the target layer to be detected by using Archie's formula or Simandoux's formula.

[0048] A logging system for quantitatively calculating the three-dimensional characterization of the resistivity of thin interbeds, comprising:

[0049] A data processing module, configured to collect the logging parameters of the target layer to be detected and perform preprocessing;

[0050] A thin interbed model characterization module, configured to establish a thin interbed model according to the logging data, and the thin interbed model is divided into four types of models according to anisotropic characteristics, including an isotropic mudstone-sandstone model, an isotropic mudstone-calcareous sandstone model, an anisotropic mudstone-sandstone model, and an anisotropic mudstone-calcareous sandstone model;

[0051] A selection module, configured to select a corresponding type of model in the thin interbed model as a calculation model according to the preprocessed logging parameters;

[0052] A calculation module, configured to input the preprocessed logging parameters into the calculation model and calculate and output the thin interbed characterization parameters of the target layer to be detected.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] The present invention provides a logging method for quantitatively calculating the three-dimensional characterization of the resistivity of thin interbeds. By collecting logging parameters of the target layer to be detected, including horizontal resistivity, vertical resistivity, and anisotropy coefficient measured by a three-dimensional induction instrument, preprocessing is carried out and combined with reference to existing logging data to establish a thin interbed model. From the anisotropic resistivity of the formation, that is, horizontal resistivity and vertical resistivity, the binary component resistivity and volume ratio of the thin interbed are extracted. According to the anisotropic resistivity formula of the thin interbed model, four types of models are proposed for characterization, namely, isotropic shale-sandstone model, anisotropic shale-sandstone model, isotropic shale-calcareous sandstone model, and anisotropic shale-calcareous sandstone model. These four types of models cover a relatively comprehensive range of resistivity anisotropy situations existing in thin interbeds. The most suitable thin interbed model for the target layer to be detected is selected according to the shale volume content and calcareous layer volume content obtained from the logging parameters for subsequent three-dimensional characterization quantitative calculation, solving the limitations of existing resistivity water saturation calculation techniques, improving the accuracy of logging water saturation calculation for complex thin interbed reservoirs, and further realizing accurate evaluation of the oil-bearing property of thin interbed reservoirs and calculation of oil and gas reserves. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 is a flow chart of the logging method for quantitatively calculating the three-dimensional characterization of the resistivity of thin interbeds according to the present invention;

[0056] Figure 2 is a schematic framework diagram of the logging system for quantitatively calculating the three-dimensional characterization of the resistivity of thin interbeds according to the present invention;

[0057] Figure 3 is a flow chart of the calculation method in the embodiment of the present invention;

[0058] Figure 4a is an isotropic shale-sandstone model in the embodiment of the present invention;

[0059] Figure 4b is an anisotropic shale-sandstone model in the embodiment of the present invention;

[0060] Figure 4c is an isotropic shale-sandstone-calcareous layer model in the embodiment of the present invention;

[0061] Figure 4d is an anisotropic shale-impurity-containing sandstone model in the embodiment of the present invention;

[0062] Figure 5 is a corrected result diagram of the resistivity of calcareous layer sandstone in the embodiment of the present invention;

[0063] Figure 6 is an interpretation result diagram of logging data in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0064] The present invention will be further described in detail below in conjunction with specific embodiments. The following is an explanation of the present invention rather than a limitation.

[0065] As Figure 1 shown, a method for quantitatively calculating logging of three-dimensional characterization of thin interbed resistivity in the present invention includes the following steps:

[0066] Collect logging parameters of the target layer to be detected and perform preprocessing;

[0067] Establish a thin interbed model based on logging data. The thin interbed model is divided into four types of models according to anisotropic characteristics, including isotropic shale-sandstone model, anisotropic shale-sandstone model, isotropic shale-calcareous sandstone model, and anisotropic shale-calcareous sandstone model;

[0068] Select a corresponding type of model in the thin interbed model as the calculation model according to the preprocessed logging parameters;

[0069] Input the preprocessed logging parameters into the calculation model, calculate and output the thin interbed characterization parameters of the target layer to be detected, and complete the three-dimensional characterization quantitative calculation logging.

[0070] The present invention provides a method for quantitatively calculating logging of three-dimensional characterization of thin interbed resistivity. By collecting logging parameters of the target layer to be detected, including horizontal resistivity, vertical resistivity, and anisotropy coefficient measured by a three-dimensional induction instrument, performing preprocessing, and combining with reference to existing logging data to establish a thin interbed model, binary component resistivity and volume ratio of the thin interbed are extracted from the anisotropic resistivity of the formation (horizontal resistivity and vertical resistivity) (determined with reference to other logging data). Based on the anisotropic resistivity formula of the thin interbed model, four types of models are proposed for characterization, namely isotropic shale-sandstone model, anisotropic shale-sandstone model, isotropic shale-calcareous sandstone model, and anisotropic shale-calcareous sandstone model. The four types of models cover a relatively comprehensive range of resistivity anisotropy situations existing in thin interbeds. Select the most suitable thin interbed model of the target layer to be detected according to the shale volume content and calcareous layer volume content obtained from the logging parameters for subsequent three-dimensional characterization quantitative calculation, solve the limitations of the existing resistivity water saturation calculation technology, improve the accuracy of calculating water saturation of complex thin interbed reservoirs by logging, and further achieve accurate evaluation of oil-bearing properties of thin interbed reservoirs and calculation of oil and gas reserves.

[0071] The specific implementation steps of the method for quantitatively calculating logging of three-dimensional characterization of thin interbed resistivity provided by the present invention are as follows:

[0072] Step 101, determine the input logging parameters:

[0073] Natural gamma ray GR, natural gamma ray spectrum U, density DEN, compensated neutron CNL, high-resolution acoustic wave HAC, three-dimensional induction horizontal resistivity Rh, vertical resistivity Rv and other curves. Among them, it is required to input at least one porosity logging curve (DEN, CNL or HAC), and it must include natural gamma ray GR, horizontal resistivity Rh and vertical resistivity curve Rv.

[0074] Step 201, determine the shale volume content (V shale ) of the thin interbed through natural gamma ray logging, and its formula is as follows:

[0075]

[0076]

[0077] In the formula, GR, GR max , GR min are the natural gamma ray value, the maximum value of natural gamma ray, and the minimum value of natural gamma ray of the target layer to be detected respectively, and GCUR is a coefficient.

[0078] Or the shale volume content (V shale ) of the thin interbed can be determined by using natural gamma ray spectrum logging, and its formula is as follows:

[0079]

[0080]

[0081] In the formula, CGR, CGR max , CGR min are the uranium-free gamma ray value, the maximum value of uranium-free gamma ray, and the minimum value of uranium-free gamma ray of the target layer to be detected respectively;

[0082] TH, TH max , TH min are the thorium curve value, the maximum value of thorium curve, and the minimum value of thorium curve of the target layer to be detected respectively;

[0083] K, K max , K min are the potassium curve value, the maximum value of potassium curve, and the minimum value of potassium curve of the target layer to be detected respectively, and GCUR is a coefficient.

[0084] Step 301, determine the calcareous layer volume content (V Ca ) of the thin interbed by using the high-resolution acoustic wave logging curve, and its formula is as follows: V Ca =Ce -0.149AC ;

[0085] In the formula, AC is the high-resolution acoustic wave logging value of the layer height, and C is a coefficient.

[0086] Step 401: Characterize the thin interbed model to implement isotropic shale - sandstone, anisotropic shale - sandstone, isotropic shale - sandstone with impurities, and anisotropic shale - sandstone with impurities models:

[0087] The first type of model: In the isotropic shale - sandstone model, in this case, there can be two actual results.

[0088] The first is to set the resistivity of shale R shale known, and calculate the resistivity of sandstone R sand and the volume V shale percentage content of laminated shale.

[0089]

[0090]

[0091] In the formula, R h is the horizontal resistivity, R v is the vertical resistivity, and R shale is the resistivity of shale.

[0092] The second is that if the shale content V shale can be obtained independently in Step 201, then the resistivity of sandstone and the resistivity of shale are respectively,

[0093]

[0094]

[0095] V sand +V shale = 1;

[0096] In the formula, R shale , R sand , V sand , V shale are respectively the resistivity of shale, the resistivity of sandstone, the volume of sandstone, and the volume of shale of the target layer to be detected. V shale is obtained according to the natural gamma curve or natural gamma energy spectrum U; R h , R v respectively represent the horizontal resistivity and vertical resistivity measured by the three - dimensional induction instrument.

[0097] The second type of model: In the anisotropic shale - sandstone model, under the condition of knowing the horizontal and vertical resistivities of shale, using the measured horizontal resistivity and vertical resistivity values R h , R v of the three - dimensional induction measurement, calculate the resistivity of sandstone R sand , where the horizontal and vertical resistivities of shale (R shale_hand R shale_v ) can be obtained in advance according to the well logging data of the representative mudstone section, and the mudstone content V shale should also be known in advance from step 201,

[0098] The volume content expression is,

[0099] V sand +V shale = 1;

[0100] The expression of sandstone resistivity is,

[0101]

[0102] The expression of mudstone resistivity is,

[0103]

[0104] Where;

[0105] In the formula, R shale , R sand , V sand , V shale are respectively the mudstone resistivity, sandstone resistivity, sandstone volume and mudstone volume of the target layer to be detected. V sand +V shale = 1, V shale is obtained by calculating according to the natural gamma curve or natural gamma energy spectrum U; R h , R v respectively represent the horizontal resistivity and vertical resistivity measured by the three-dimensional induction instrument; R shale-h , R shale-v respectively represent the horizontal resistivity of the mudstone of the target layer to be detected and the vertical resistivity of the mudstone of the target layer to be detected obtained according to the well logging data of the mudstone section.

[0106] The third type of model: In the isotropic mudstone-calcareous sandstone model, it is obtained by combining isotropic mudstone, isotropic sandstone and calcareous layer. In this case, the mudstone resistivity R shale is known, and the sandstone resistivity R sand , the calcareous layer resistivity R ca and the volume V of the laminated mudstone shale percentage content are calculated.

[0107] The transformation processing formula of the isotropic mudstone-calcareous sandstone model,

[0108] V sand +V shale +V ca = 1;

[0109] When Rv >R h When

[0110] R v =R shale V shale +R sand V sand +R ca V ca ;

[0111] Wherein, R shale , R sand , V shale , V sand , R ca , V ca are respectively the shale resistivity, sandstone resistivity, shale volume, sandstone volume, calcareous layer resistivity and calcareous layer shale volume of the target layer to be detected. V shale is obtained by calculating according to the natural gamma curve or natural gamma ray spectrometry U; R shale is obtained according to the logging data of the shale section; R h , R v respectively represent the horizontal resistivity and vertical resistivity measured by a three-dimensional induction instrument;

[0112] The calcareous layer resistivity R ca and the calcareous layer shale volume V ca obtained by calculating according to the above formula are used to transform the measured R h , R v to obtain the horizontal resistivity R h ' and vertical resistivity R v ' in the isotropic shale-calcareous sandstone model, and their expressions are respectively,

[0113]

[0114]

[0115] The fourth type of model: In the anisotropic shale-calcareous sandstone model, under the condition that the horizontal and vertical resistivities of the known shale are set, the horizontal resistivity and vertical resistivity values R h , R v measured by three-dimensional induction are used to calculate the sandstone resistivity R sand , where the horizontal and vertical resistivities of the shale (R shale_h and R shale_v ) can be obtained in advance according to the logging data of the representative shale section, and the shale content V shale and the calcareous layer content V ca are known in advance from step 201,

[0116] The transformation processing formula for the anisotropic mudstone - calcareous sandstone model

[0117] V sand +V shale +V ca = 1;

[0118]

[0119] R v -R ca V ca = R shale-v V shale +R sand V sand ;

[0120] In the formula, R shale , R sand , V shale , V sand , R ca , V ca are respectively the resistivity of mudstone, the resistivity of sandstone, the volume of mudstone, the volume of sandstone, the resistivity of calcareous layer, and the volume of mudstone in the calcareous layer of the target layer to be detected. V shale and V ca are obtained by calculating according to the natural gamma curve or natural gamma energy spectrum U; R h , R v respectively represent the horizontal resistivity and vertical resistivity measured by a three - dimensional induction instrument; R shale-h , R shale-v respectively represent the horizontal resistivity of mudstone in the target layer to be detected and the vertical resistivity of mudstone in the target layer to be detected obtained from the logging data of the mudstone section;

[0121] The resistivity R ca of the calcareous layer and the volume of mudstone V ca in the calcareous layer obtained by calculating according to the above formula are used to transform the measured R h , R v to obtain the horizontal resistivity R” h and vertical resistivity R” v in the anisotropic mudstone - calcareous sandstone model, and their expressions are respectively,

[0122]

[0123]

[0124] Step 501: Select a suitable thin - interbed model as the calculation model for saturation according to the logging parameter results obtained above to calculate the saturation under the reservoir conditions, and generate the thin - interbed sandstone water saturation corresponding to different logging depths. The specific steps include,

[0125] Step 502: Select one of the four models: isotropic shale-sandstone model, anisotropic shale-sandstone model, isotropic shale-calcareous sandstone model, and anisotropic shale-calcareous sandstone model, and calculate and determine the sandstone resistivity and sandstone volume according to the calculation expression;

[0126] Step 503: Calculate the total porosity by combining density logging and neutron logging;

[0127]

[0128] Among them, the density logging DEN is used to calculate and obtain

[0129] The compensated neutron CNL is used to calculate and obtain

[0130] Step 504: Calculate the effective porosity:

[0131] Step 505: Through the following saturation calculation formula, applying Archie or Simandoux formula and the anisotropic formation model in Step 101, the sandstone resistivity for three-dimensional bulk resistivity characterization can be generated respectively, and the water saturation is calculated:

[0132]

[0133] In the formula, S w is the water saturation, a represents the lithology coefficient related to lithology, b represents the constant related to lithology, m is the cementation coefficient, n is the saturation exponent, φ eff is the effective porosity, R w is the formation water resistivity, R sd is the formation water resistivity;

[0134] Or

[0135] In the formula, S w is the water saturation, φ eff is the effective porosity, R w is the formation water resistivity, R sd is the formation water resistivity, V sh is the volume of the shale layer content, R sh is the resistivity of the shale layer.

[0136] To achieve the above object, according to the thin interbed resistivity three-dimensional characterization quantitative calculation logging method described in the present invention, as Figure 2 shown, the present invention also provides a thin interbed resistivity three-dimensional characterization quantitative calculation logging system, including,

[0137] A data processing module for collecting well logging parameters of the target layer to be detected and performing preprocessing;

[0138] A thin interbed model characterization module for establishing a thin interbed model based on well logging data. The thin interbed model is divided into four types according to anisotropic characteristics, including an isotropic shale-sandstone model, an isotropic shale-calcareous sandstone model, an anisotropic shale-sandstone model, and an anisotropic shale-calcareous sandstone model;

[0139] A selection module for selecting a corresponding type of model in the thin interbed model as the calculation model according to the preprocessed well logging parameters;

[0140] A calculation module for inputting the preprocessed well logging parameters into the calculation model and calculating and outputting the thin interbed characterization parameters of the target layer to be detected.

[0141] Embodiment

[0142] The present invention provides a specific embodiment to further explain and illustrate the present invention according to the above-mentioned method for quantitatively calculating well logging by three-dimensional characterization of thin interbed resistivity.

[0143] An embodiment of the present invention provides a method for three-dimensional characterization and quantitative calculation of thin interbed resistivity. The process of this calculation method mainly consists of 4 links, mainly including the following steps: input of original well logging data S101, well logging preprocessing S201, sandstone and shale formation model characterization S300, and sandstone and shale formation saturation calculation S401.

[0144] Input well logging curves 101, including inputting preprocessed well logging parameters: natural gamma ray GR, density DEN, compensated neutron CNL, acoustic wave AC, three-dimensional induction horizontal resistivity Rh, vertical resistivity Rv and other curves.

[0145] Among them, it is necessary to input and select natural gamma ray GR, horizontal resistivity Rh and vertical resistivity curve Rv, and at least one porosity well logging curve should be input.

[0146] Calculation of thin interbed volume content 201, through the input well logging curve 101 unit, complete the preprocessing of well logging data, specifically including calculation of shale volume content, calcareous layer volume content, formation porosity and anisotropy. Among them, use natural gamma ray well logging to determine the shale volume content (V shale ) of the thin interbed. At the same time, the shale volume content (V shale ) of the thin interbed can be determined by using natural gamma ray spectroscopy well logging. Use high-resolution acoustic wave well logging curve to determine the calcareous layer volume content (V Ca), the density DEN and compensated neutron CNL are used to calculate the porosity, the anisotropy coefficient λ is calculated using the horizontal resistivity and vertical resistivity, and the data such as the volume content and other resistivities calculated by well logging preprocessing are sent to S300, the sand-shale thin interbed formation model characterization unit;

[0147] The sand-shale thin interbed formation model characterization unit S300 realizes the isotropic shale-sandstone S301, the anisotropic shale-sandstone S302, the isotropic shale-calcareous layer-sandstone S303, and the anisotropic shale-impurity-bearing sandstone model S304.

[0148] Select the isotropic shale-sandstone model S301. First, set the shale resistivity R shale Known, the sandstone resistivity R is calculated sand and the volume V of laminated shale shale Percentage content, or it can also be the shale content V shale Can be obtained independently, then the sandstone resistivity and shale resistivity are:

[0149]

[0150]

[0151] V sand +V shale =1, where R shale 、R sand 、V sand Are the shale resistivity, sandstone resistivity, and sandstone volume of the target layer.

[0152] Select the anisotropic shale-sandstone model S302. Under the condition of known horizontal and vertical resistivities of shale, use the horizontal resistivity and vertical resistivity values R h 、R v Measured by three-dimensional induction to calculate the sandstone resistivity R sand , where the horizontal and vertical resistivities of shale (R shale_h and R shale_v ) must be obtained in advance according to the well logging data of representative shale sections, and the shale content V shale Should also be known in advance from step (201). The horizontal resistivity of shale, vertical resistivity of shale, sandstone resistivity, and sandstone volume of the target layer are output according to the following formula:

[0153] V sand +V shale =1,α=R shale-v / R shale-h

[0154] Where R v >R h, where where

[0155] In the formula, R shale_h , R shale_v , R sand , V sand are the horizontal resistivity of the target layer mudstone, the vertical resistivity of the mudstone, the resistivity of the sandstone, and the sandstone volume.

[0156] Select the mudstone-sandstone-calcareous layer calculation model S303. In isotropic mudstone, isotropic sandstone, and calcareous layer, in this case, set the mudstone resistivity R shale known, calculate and output the sandstone resistivity R sand , the calcareous layer resistivity R ca and the percentage content of the laminated mudstone volume V shale .

[0157] Select the mudstone-sandstone-calcareous layer calculation model S304. Under the condition of known horizontal and vertical resistivities of the mudstone, use the horizontal resistivity and vertical resistivity values R h , R v of the three-dimensional induction measurement to calculate the sandstone resistivity R sand , where the horizontal and vertical resistivities of the mudstone (R shale_h and R shale_v ) must be obtained in advance according to the well logging data of the representative mudstone section. The mudstone content V shale and the calcareous layer content V ca are known in advance by step (201). According to the transformation processing formula of the anisotropic mudstone-sandstone-calcium layer model, output the horizontal resistivity of the target layer mudstone, the vertical resistivity of the mudstone, the resistivity of the sandstone, the resistivity of the calcareous interlayer, the sandstone volume, and the calcareous layer volume.

[0158] The saturation calculation unit S400 first uses the thin interbed volume content calculation S201, combines the density logging and neutron logging curves to calculate the effective porosity, and according to the sandstone-mudstone thin interbed formation model characterization unit S300, selects the sandstone resistivity R sand data and the mudstone resistivity R shale data of the sandstone-mudstone thin interbed formation model and inputs them into the next-level saturation calculation unit S401.

[0159] The steps of generating the thin interbed sandstone saturation index corresponding to different logging depths for the saturation calculation model under the reservoir conditions using the established saturation model include:

[0160] Step S401, through rock physics experiments, input and determine the formation electro-formation parameters (m, n) and R w formation water resistivity value;

[0161] Step 402, calculate the fluid saturation by applying Archie's formula:

[0162]

[0163] where a and b are lithology coefficients, m is the cementation coefficient, n is the saturation exponent, and φ eff is the effective porosity, R w is the formation water resistivity, and R sand is the sandstone resistivity data.

[0164] Calculate the fluid saturation by applying Simandoux's formula:

[0165]

[0166] where φ eff is the effective porosity, R w is the formation water resistivity, R sand is the sandstone resistivity data, and R shale is the mudstone resistivity data.

[0167] Step 403, finally output the true formation sandstone resistivity R sand , the proportion of mudstone volume V shale , the total porosity φ t , the effective porosity φ eff , the reservoir saturation S w and the formation anisotropy λ, thus completing the whole process of three-dimensional characterization and quantitative calculation of thin interbed resistivity.

[0168] All the content of the unit for three-dimensional characterization and quantitative calculation of thin interbed resistivity provided by the embodiments of the present invention can be implemented by software programming, and the function of generating logging data results printing, exporting, and generating pictures is completed for the output of processing and interpretation result curves. Its software program is stored in a readable storage medium, such as a hard disk, optical disc, or floppy disk in a computer.

[0169] As Figures 4a to 4d shown, four formation models for three-dimensional characterization of thin interbed resistivity are established, namely, isotropic mudstone-sandstone model Figure 4a , anisotropic mudstone-sandstone model for three-dimensional characterization of thin interbed resistivity Figure 4b , isotropic mudstone-sandstone-calcareous layer model for three-dimensional characterization of thin interbed resistivity Figure 4c and anisotropic mudstone-impurity-containing sandstone model for three-dimensional characterization of thin interbed resistivity Figure 4d .

[0170] Figure 5This is the resistivity simulation result of calcareous sandstone. Figure 5 It can be seen that under the given horizontal resistivity, vertical resistivity, mudstone resistivity and sandstone volume, the sensitivity curve analysis shows that the sandstone resistivity and calcium content volume ratio of this model change linearly, and the change rate is very sensitive to the change of calcium resistivity. It is very easy to have the non-physical situation of zero and negative values of sandstone resistivity, which is a serious defect of this model and limits the application of this algorithm.

[0171] So in Figure 4c The mudstone-sandstone calcareous mixed layer model is based on the basic assumption that sandstone contains calcium and calcium and sand are evenly mixed. The resistivity of sandstone is calculated in two steps:

[0172] In the first step, the resistivity of the mixed layer is calculated using the mudstone-equivalent sandstone model;

[0173] In the second step, the resistivity parallel model is used to obtain the resistivity of sandstone. In the model, the resistivity of calcium is selected as infinite to eliminate the influence of this parameter. The resistivity of sandstone is proportional to the resistivity of the mixed layer and changes positively with the volume proportion of sandstone in the mixed layer.

[0174] The present invention considers the correction factor q introduced to take into account the factors of non-uniform mixing of sand and mud, which should be given by data processing and well logging geological data experience.

[0175]

[0176] Depend on Figure 6 The results of the measured data processing show that Figure 6 The first channel is the depth channel, and the selected well section is between 1820-1855m.

[0177] The second track is the lithology curve, which contains natural gamma ray (GR), natural potential (SP), and wellbore (CAL). The GR value of mudstone is relatively high, while that of sandstone is relatively low. The GR value increases with the increase of mud content. There are many layers with relatively high GR values in the No. 29 and No. 32 reservoir sections, indicating the development of mud interlayers in the sandstone reservoir.

[0178] The fifth track is a three-dimensional induction resistivity comparison track. The AT90 in the track is the array induction resistivity of 2in longitudinal and 90in radial. h is the three-dimensional induced horizontal resistivity, R v is the three-dimensional induced vertical resistivity, and the filling is based on R h is a left curve, R vFilled for the right curve, the filling represents the horizontal and vertical resistivity differences. In the reservoir, the resistivity in different directions responds significantly to the fluid properties. The resistivity difference of a single fluid is small, while that of a miscible fluid is large. In the figure, layer 28 is a poor oil layer with less movable fluid and a small difference in single vertical and horizontal resistivity. Layers 29 and 30 are oil-water layers, and layer 31 is an oil-bearing water layer. The fluid is an oil-water miscible fluid with a large difference in vertical and horizontal resistivity. Layer 32 is a water layer, and the fluid is formation water, with the horizontal and vertical resistivity almost overlapping.

[0179] The sixth trace is the sandstone-mudstone resistivity trace, R SA is the sandstone resistivity inverted by applying the present invention, R SH is the mudstone resistivity, with a relatively high value in the sandstone section and a relatively low value in the mudstone section.

[0180] The seventh trace is the oil-gas analysis trace. The sandstone water saturation is the sandstone water saturation calculated using the Archie formula with the sandstone resistivity R SA as the formation resistivity. The filled part is the horizontal and vertical resistivity anisotropy. In the reservoir, the resistivity anisotropy responds significantly to the fluid properties. The resistivity anisotropy of a single fluid is weak, while that of a miscible fluid is strong. In the figure, layer 28 is a poor oil layer with less movable fluid and a weak resistivity anisotropy of a single fluid. Layers 29 and 30 are oil-water layers, and layer 31 is an oil-bearing water layer. The fluid is an oil-water miscible fluid with a strong electrical anisotropy. Layer 32 is a water layer, and the fluid is formation water, with the resistivity showing isotropy.

[0181] From the results obtained through the embodiments, it can be seen that the method described in the present invention can improve the accuracy of logging saturation calculation for complex sandstone-mudstone reservoirs, and achieve accurate evaluation of the oil-bearing property of thin interbedded reservoirs and calculation of oil-gas reserves.

[0182] To achieve the above object, the main technical means adopted in the present invention shall be clearly, completely and accurately described, and the essential content of the invention shall be explained. The degree of disclosure shall be such that those of ordinary skill in the art can understand and implement it.

Claims

1. A quantitative calculation logging method for three-dimensional characterization of resistivity of thin interbeds, characterized in that, It includes the following steps: Collect well logging parameters of the target layer to be detected and perform preprocessing; Establish a thin interbed model based on well logging data. The thin interbed model is divided into four types of models according to anisotropic characteristics, including isotropic shale-sandstone model, anisotropic shale-sandstone model, isotropic shale-calcareous sandstone model, and anisotropic shale-calcareous sandstone model; Select a corresponding type of model in the thin interbed model as the calculation model according to the preprocessed well logging parameters; Input the preprocessed well logging parameters into the calculation model, calculate and output the thin interbed characterization parameters of the target layer to be detected, and complete the stereoscopic characterization quantitative calculation well logging; The expression of the isotropic shale-sandstone model includes the expression of sandstone resistivity and the expression of shale resistivity: The expression of sandstone resistivity is The expression of shale resistivity is Wherein, R shale , R sand , V sand , V shale are respectively the resistivity of shale, the resistivity of sandstone, the volume of sandstone, and the volume of shale of the target layer to be detected. Among them, V sand +V shale =1, V shale is obtained by calculating according to the natural gamma curve or natural gamma energy spectrum U; R h , R v respectively represent the horizontal resistivity and the vertical resistivity measured by a three-dimensional induction instrument; The expression of the anisotropic shale-sandstone model includes the expression of sandstone resistivity and the expression of shale resistivity: The expression of sandstone resistivity is The expression of shale resistivity is where; α = R shale-v / R shale-h ; Wherein, R shale , R sand , V sand , V shale are respectively the resistivity of mudstone, the resistivity of sandstone, the volume of sandstone, and the volume of mudstone of the target layer to be detected. V sand +V shale = 1. V shale is obtained by calculating according to the natural gamma curve or the natural gamma energy spectrum U; R h , R v respectively represent the horizontal resistivity and the vertical resistivity measured by a three-dimensional induction instrument; R shale-h , R shale-v respectively represent the horizontal resistivity of the mudstone of the target layer to be detected and the vertical resistivity of the mudstone of the target layer to be detected obtained according to the logging data of the mudstone section; The expression of the isotropic shale-calcareous sandstone model includes: V sand +V shale +V ca = 1; R v = R shale V shale + R sand V sand + R ca V ca ; Wherein, R shale , R sand , V shale , V sand , R ca , V ca are respectively the resistivity of shale, the resistivity of sandstone, the volume of shale, the volume of sandstone, the resistivity of calcareous layer and the shale volume of calcareous layer of the target layer to be detected, V shale is obtained by calculating according to the natural gamma curve or natural gamma energy spectrum U; R shale is obtained according to the logging data of the shale section; R h , R v respectively represent the horizontal resistivity and the vertical resistivity measured by using a three-dimensional induction instrument; The resistivity R of the calcareous layer obtained by calculating according to the above expression ca and the volume V of the calcareous shale ca Convert the measured Rh and Rv to obtain the horizontal resistivity R' and the vertical resistivity R' in the isotropic shale-calcareous sandstone model h respectively, and their expressions are as follows: v , and their expressions are respectively: The expression of the anisotropic shale-calcareous sandstone model includes: V sand +V shale +V ca = 1; R v -R ca V ca =R shale-v V shale +R sand V sand ; Wherein, R shale and R sand , V shale , V sand , R ca , V ca are respectively the resistivity of mudstone, the resistivity of sandstone, the volume of mudstone, the volume of sandstone, the resistivity of calcareous layer and the volume of mudstone in the calcareous layer of the target layer to be detected, V shale and V ca are obtained by calculating according to the natural gamma curve or natural gamma energy spectrum U; R h and R v respectively represent the horizontal resistivity and vertical resistivity measured by a three-dimensional induction instrument; R shale-h and R shale-v respectively represent the horizontal resistivity of mudstone in the target layer to be detected and the vertical resistivity of mudstone in the target layer to be detected obtained according to the logging data of the mudstone section; The resistivity R of the calcium layer calculated according to the above expression ca and the volume of calcareous mudstone V ca The measured R h , R v Transform to obtain the horizontal resistivity R" in the anisotropic mudstone-calcareous sandstone model h and vertical resistivity R” v , whose expressions are:

2. The quantitative calculation logging method for three-dimensional characterization of resistivity of thin interbeds according to claim 1, wherein, The well logging parameters collected for the target layer to be detected include three-dimensional induction resistivity curve, natural gamma curve GR, natural gamma energy spectrum U, and at least one porosity well logging curve.

3. The logging method for quantitative calculation of three-dimensional characterization of resistivity of thin interbeds according to claim 2, characterized in that The three-dimensional induction resistivity curve includes three-dimensional induction horizontal resistivity curve Rh and three-dimensional induction vertical resistivity curve Rv; The porosity well logging curve includes density curve DEN, compensated neutron curve CNL, and high-resolution acoustic curve HAC.

4. A logging method for quantitative calculation of three-dimensional characterization of resistivity of thin interbeds according to claim 2, characterized in that, The preprocessing of the well logging parameters collected for the target layer to be detected includes Calculating and obtaining the shale volume of the target layer to be detected according to the natural gamma curve or natural gamma energy spectrum U; Calculating and obtaining the calcareous layer volume content and porosity of the target layer to be detected according to the porosity well logging curve; Calculating and obtaining the anisotropy coefficient of the target layer to be detected according to the three-dimensional induction resistivity curve.

5. A logging method for quantitative calculation of three-dimensional characterization of resistivity of thin interbeds according to claim 1, characterized in that, Inputting the preprocessed well logging parameters into the calculation model and calculating and outputting the thin interbed characterization parameters of the target layer to be detected includes calculating the water saturation of the target layer to be detected using Archie's formula or Simandoux's formula.

6. A logging system for quantitative calculation of three-dimensional characterization of resistivity of thin interbeds, characterized in that, The well logging method according to any one of claims 1-5 includes: A data processing module for collecting well logging parameters of the target layer to be detected and performing preprocessing; A thin interbed model characterization module for establishing a thin interbed model based on well logging data. The thin interbed model is divided into four types of models according to anisotropic characteristics, including isotropic shale-sandstone model, isotropic shale-calcareous sandstone model, anisotropic shale-sandstone model, and anisotropic shale-calcareous sandstone model; A selection module for selecting a corresponding type of model in the thin interbed model as the calculation model according to the preprocessed well logging parameters; A calculation module for inputting the preprocessed well logging parameters into the calculation model and calculating and outputting the thin interbed characterization parameters of the target layer to be detected.

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