CN109635410B - Permeability discrete element simulation method based on pore system - Google Patents
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Abstract
The invention provides a permeability discrete element simulation method based on a pore system, which comprises the following steps: measuring the average permeability and a gas adsorption-desorption curve of a reservoir where a research object is located in a research area; determining the type of pores according to the gas adsorption-desorption curve obtained in the step 1; simplifying the pore types obtained in the step 2 to obtain a discretized pore size model; calculating the basic statistical parameters of the pore size distribution of the discretization pore size model obtained in the step 3; converting the discretization aperture module obtained in the step 3 into a permeability discrete element according to the basic statistical parameters of the aperture distribution of the discretization aperture model obtained in the step 4; expanding and embedding the permeability discrete element obtained in the step (5) into a reservoir where the research object is located to obtain a permeability discrete element model of the reservoir where the research object is located in the research area; the method can better meet the actual requirements of oil gas/geothermal exploration and development, particularly in reservoirs with remarkable difference of permeability.
Description
Technical Field
The invention belongs to a numerical simulation technology in a geological exploration and development technology, and particularly relates to a permeability discrete element simulation method based on a pore system.
Background
Permeability is an important parameter in oil and gas, geothermal and hydrogeological research, and plays a crucial role in oil and gas migration and heat flow transfer. Therefore, permeability distribution is an essential element of geological modeling, especially in terms of fluid migration, and its accurate setting becomes an important step in optimizing the favorable zone for oil and gas exploration, determining the oil and gas/geothermal spread characteristics of the next step, and the like. Only by effectively determining the permeability distribution rule of the main oil and gas reservoir or geothermal reservoir, a reliable geological evaluation model can be established, and correct technical guidance is provided for later reservoir evaluation and production decision.
In the existing numerical simulation method, the most common method is to set the reservoir permeability in the model to a single fixed value based on an actually measured permeability mean value, and carry out numerical simulation work on the basis; however, the difference between the actual geological situation and the simulation result is far from the actual background. Partial scholars give random number permeability values to each cell of the reservoir by adopting a random means; however, the random distribution characteristics do not have practical geological significance, and the calculated numerical result has poor geological interpretability.
With the continuous progress of pore size distribution research means, the type of a pore system and the pore size distribution characteristics of a reservoir can be known through gas adsorption-desorption experiments and other means, and the pore system can be further determined to be a two-side opening type, an ink bottle type, a parallel slit type or a single-side slit type. However, the pore size distribution characteristics have not been applied to permeability distribution studies, and have not been applied to high-precision numerical simulation.
Therefore, a new permeability discrete element simulation method which refers to pore size distribution characteristics and more effectively represents the permeability distribution of the reservoir is needed to be formed so as to meet the actual requirements of early exploration of oil gas, geothermy and the like.
According to the method, a permeability discrete element simulation method is provided for the first time in China based on the type of a pore system, pore diameter data are embedded, permeability parameter distribution characteristics are effectively traced, the reservoir permeability distribution rule can be further deepened on the basis of gas adsorption-desorption experiment data, and the precision of a numerical simulation result is improved.
Disclosure of Invention
The invention aims to provide a permeability discrete element simulation method based on a pore system, which solves the problem that the existing geological modeling is poor in geological interpretation caused by inaccurate permeability value.
In order to achieve the purpose, the invention adopts the technical scheme that:
the invention provides a permeability discrete element simulation method based on a pore system, which comprises the following steps:
step 1, measuring the average permeability and a gas adsorption-desorption curve of a reservoir where a research object is located in a research area;
step 2, determining the type of pores according to the gas adsorption-desorption curve obtained in the step 1;
step 3, simplifying the pore types obtained in the step 2 to obtain a discretized pore size model;
step 4, calculating the basic statistical parameters of the pore size distribution of the discretization pore size model obtained in the step 3;
step 5, converting the discretization aperture module obtained in the step 3 into a permeability discrete element according to the basic statistical parameters of the aperture distribution of the discretization aperture model obtained in the step 4;
and 6, expanding and embedding the permeability discrete element obtained in the step 5 into a reservoir where the research object is located to obtain a permeability discrete element model of the reservoir where the research object is located in the research area.
Preferably, first, m samples of different positions and depths of the stratum where the study object is located in the study area are collected, and the permeability of each sample is measured and recorded as k1、k2、k3……km；
Secondly, calculating the permeability mean value of the corresponding reservoir stratum by using the formula (1)
Preferably, the specific method for converting the original aperture model into the discretized aperture model is as follows:
firstly, drawing an original aperture model according to the characteristics of different aperture models obtained in the step 2;
secondly, setting the total length of the original aperture model as d and unit nm; the original aperture model comprises n discrete element combination units, and the length corresponding to each discrete element combination unit is
Next, the average pore size r of the ith discrete element combination cell is calculated according toi：
Wherein S isiThe area actually covered by the aperture in the ith discrete unit;
finally, according to the aperture r of each discrete element combination unit obtained aboveiAnd splicing and drawing the discretization aperture combination model.
Preferably, the specific method for calculating the basic statistical parameters of the pore size distribution of the discretized pore size model obtained in the step 3 is as follows:
setting the discrete element aperture model obtained in the step 2 to comprise n discrete element combination units, wherein the aperture in each discrete element combination unit is r1、r2、r3……rnIn nm, the main statistical parameters can be expressed as:
wherein the content of the first and second substances,
the mean value of the aperture of the discrete element aperture model is unit nm; σ (r) refers to the standard deviation of the aperture of the discrete element aperture model, in nm; cv () refers to the coefficient of variation of the discrete meta-aperture model.
Preferably, a specific method for converting the discretization aperture model combination obtained in the step 3 into the permeability discrete element model combination is as follows:
firstly, setting a permeability discrete element model combination comprising n' permeability discrete elementsThe permeability of each permeability discrete unit in the permeability discrete element model combination is sequentially expressed as
The unit mD;
wherein the average permeability of the permeability discrete element model combination
The following relationship should be satisfied:
the permeability variation coefficient of the permeability discrete element model combination
The following relationship should be satisfied:
standard deviation of the permeability discrete element model combination
It is further expressed as:
secondly, complement specific conditional relationships according to different pore structures, wherein assuming that a discrete element combination contains 2 discrete units of permeability, then:
if the pore system is open on both sides, the relationship should be satisfied:
if the pore system is an ink bottle, the relationship is satisfied:
if the pore system is of the parallel slit type, the relationship is satisfied:
if the pore system is of the single-sided slit type, the relationship is satisfied:
assuming that the discrete element combination contains 2+1 permeability discrete units, then:
if the pore system is open on both sides, the relationship should be satisfied:
if the pore system is an ink bottle, the relationship is satisfied:
if the pore system is of the parallel slit type, the relationship is satisfied:
if the pore system is of the single-sided slit type, the relationship is satisfied:
finally, through the simultaneous formulas (5) - (11), the permeability value corresponding to each discrete element combination unit in the discrete element combination is solved
Preferably, the permeability discrete elements obtained in the step 5 are expanded and embedded into the reservoir where the research object is located in a horizontal repetition or longitudinal repetition mode.
Compared with the prior art, the invention has the beneficial effects that:
according to the permeability discrete element simulation method based on the pore system, provided by the invention, gas adsorption-desorption experiment parameters are combined with actually measured permeability data, the permeability distribution characteristics of the reservoir can be more reliably represented according to the type of the pore system, and the actual requirements of oil gas/geothermal exploration and development, particularly oil gas/geothermal development in the reservoir with obvious difference in permeability, can be better met.
Drawings
FIG. 1 is a flow chart of a permeability discrete element simulation in the present invention;
FIG. 2 is a schematic illustration of a pore system of the type used in the present invention;
FIG. 3 is a schematic diagram of the conversion of the pore discrete elements into permeability discrete elements in the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
As shown in fig. 1, the invention provides a permeability discrete element simulation method based on a pore system, comprising the following steps:
the method comprises the following steps of firstly, determining the simulation type of each stratum in a research area, wherein the simulation type comprises a fine simulation and a simplified simulation:
firstly, determining a research object in a research area, and determining the simulation type of a stratum where the research object is located as a refined simulation; determining the simulation type of other strata in the research area as simplified simulation;
step two, determining the average permeability of the reservoir:
firstly, collecting a plurality of samples of different positions and different depths of a stratum where a research object is positioned, measuring the permeability of each sample, and respectively recording the permeability as k1、k2、k3……km；
Secondly, calculating the permeability mean value of the corresponding reservoir stratum by using the formula (1)
Step three, acquiring a gas adsorption-desorption curve, and determining the type of the pore:
first, a sample in the reservoir is collected and a gas (generally referred to as N) is developed according to the standard "specific surface area of rock and pore size distribution measurement static nitrogen adsorption capacity method (SY/T6154-1995)"2、CO2Etc.) an adsorption-desorption experiment, and acquiring an adsorption-desorption curve of a corresponding sample;
secondly, according to the obtained adsorption-desorption curve and the combination of research results related to the pure and applied chemical international association (IUPAC), judging that the adsorption-desorption curve belongs to H1、H2、H3Or is H4A type;
and finally, determining the pore type of the reservoir according to the type of the adsorption-desorption curve, wherein the pore type comprises a two-side opening type, an ink bottle type, a parallel slit type and a single-side slit type (figure 2).
Step four, simplifying pore types, and representing pore size distribution in a discretization mode:
in order to characterize the influence of the pore system on the reservoir permeability in the discrete element model, the original pore size model needs to be converted into a discretized pore size model, specifically:
firstly, drawing an original aperture model (figure 3) according to different aperture model characteristics described by the pure and applied chemical international association (IUPAC), wherein the total length of the aperture model is d and the unit is nm; secondly, setting the original aperture modeThe total length of the form is d in nm; the original aperture model comprises n discrete element combination units, and the length corresponding to each discrete element combination unit is
Next, the average pore size r of the ith discrete element combination cell is calculated according toi：
Wherein S isiThe area actually covered by the aperture in the ith discrete element combination unit;
finally, according to the aperture r of each discrete element combination unit obtained aboveiSplicing and drawing a discretization aperture combination model (figure 3);
step five, calculating the basic statistical parameters of the pore size distribution: in order to reflect the characteristics of the pore size distribution on the permeability characteristics, the main statistical parameters of the pore size distribution need to be calculated first. Assuming that the aperture discrete element model combination comprises n aperture discrete element combination units, the aperture in each aperture discrete element combination unit is r1、r2、r3……rnIn nm. The main statistical parameters can be expressed as:
in the above formula, the first and second carbon atoms are,
the mean value of the pore diameters in a discrete element combination can reflect the average pore diameter level of a reservoir in a model in unit nm; sigma (r) refers to the standard deviation of the aperture, reflecting the variation amplitude of the aperture in nm; and cv () refers to the coefficient of variation in the discrete element combination, which reflects the degree of dispersion of the aperture under dimensionless premise. All the indexes can provide reference basis for establishing the permeability discrete element.
Step six, converting the aperture discrete element into a permeability discrete element: assuming that each permeability discrete element combination comprises n permeability discrete units, the permeability of the permeability discrete units in the combination is sequentially expressed as
Etc., in the unit mD. In order to ensure that the average permeability of the permeability discrete element combination is consistent with the overall permeability of the reservoir in the model, the following relational expression is satisfied:
in the formula (I), the compound is shown in the specification,
represents the mean permeability in discrete element combinations in mD.
Meanwhile, in order to make the dispersion degree of the permeability discrete element substantially consistent with the dispersion degree of the pore size distribution, the permeability discrete element should also satisfy the formula:
in the formula (I), the compound is shown in the specification,
representing the permeability coefficient of variation in discrete element combinations, dimensionless. Wherein the standard deviation of the permeability discrete element
Can be further expressed as:
the unit mD.
In addition, since different pore systems have different pore size distribution characteristics, specific condition relationships are supplemented for different pore structures. Assuming that the discrete element combination comprises 2 discrete units of permeability, if the pore system is of the two-sided open type (H)1Type), then the relation should be satisfied:
if the pore system is of the ink bottle type (H)2Type), then the relation should be satisfied:
if the pore system is of the parallel slit type (H)3Type), then the relation needs to be satisfied:
if the pore system is of the single-sided slit type (H)4Type), then it should be guaranteed:
assuming that the discrete element combination comprises 2+1 discrete elements of permeability, if the pore system is of the two-sided open type (H)1Type), then the relation should be satisfied:
if the pore system is of the ink bottle type (H)2Type), then the relation should be satisfied:
if the pore system is of the parallel slit type (H)3Type), then the relation needs to be satisfied:
if the pore system is of the single-sided slit type (H)4Type), then it should be guaranteed:
through the simultaneous formulas (5) - (15), the permeability value corresponding to each discrete unit in the discrete element combination can be solved
Etc. (fig. 3).
Step seven, extrapolating the permeability discrete element to the whole simulation system: due to the limited discrete units involved in the permeability discrete element combination, it is necessary to extrapolate the discrete units to the entire reservoir model. Therefore, the permeability discrete unit capable of reflecting pore system pore size distribution can be expanded to the whole fluid reservoir through horizontal repetition, longitudinal repetition and other modes so as to be embedded into the whole simulation system; the whole simulation system is TOUGH series software which is used for simulating numerical simulation programs of multiphase flow, multi-component and non-Duvenn fluid flow, heat transfer and pollutant migration in one-dimensional, two-dimensional and three-dimensional porous fracture media.
In order to make the person skilled in the art understand the method for discrete element simulation of permeability based on pore system in the present invention more deeply, the method for discrete element simulation of permeability in the present invention will be further described in detail with reference to the flow chart (fig. 1) by taking region a as an example.
Step one, determining a geological system to be simulated and a corresponding reservoir: before carrying out numerical simulation work, a research area to be simulated, a research object and a corresponding reservoir stratum are determined. The area A is a shale gas block in the southeast area of Chongqing Yu, and the main shale gas exploration and development layer in the research area is a lower Hanwu system cow-hoof pond group, and the burial depth is about 3000-4000 m. According to the disclosure of shale gas drilling exploration wells of wells B in the area A, the overall thickness of a cow hoof pond group is about 125m, the corresponding depth of a reservoir layer of a target layer at the bottom is 3802-. Thus, it can be basically determined that: the area A is a research area, a high-quality reservoir about 40m at the bottom of the cow-foot pond group is an important shale gas reservoir needing fine simulation, and other upper and lower strata can be simply treated.
Step two, determining the average permeability of the reservoir: selecting 29 shale samples of the cow-hoof pond group with the depth corresponding to the depth of 3802-3842m of the B well for carrying out permeability analysis and test, and calculating the average permeability of the corresponding target layer by using a formula (1)
Since the research area has no other research horizons, the average permeability of other shale gas reservoirs does not need to be calculated.
TABLE 1B well 3802-
Step three, acquiring a gas adsorption-desorption curve, and determining the type of the pore: selecting B well 3802-2The adsorption-desorption experiment is easy to find: n corresponding to deep shale sample2The adsorption curve and the desorption curve almost coincide, and the whole adsorption-desorption curve is relatively flat, according to the IUPAC research result, the adsorption-desorption curve is indicated to belong to H4The type of the corresponding pore is a single-side slit type.
Step four, simplifying pore types, and representing pore size distribution in a discretization mode: according to the third step, the pore type of the target layer of the cattle hoof pond group in the area A can be determined to be a unilateral slit type. Meanwhile, the primary micropores have a pore size of about 5nm, according to the pore size analysis of the study area. In the discrete element combination containing 3 discrete units, the aperture of each discrete element can be set to r1＝1nm、r25nm and r39nm, which is suitable for discrete element aperture model combination of numerical simulation.
Step five, calculating the basic statistical parameters of the pore size distribution: from the above aperture combination comprising 3 discrete units, the aperture mean can be calculated
Comprises the following steps:
the standard deviation σ (r) of the aperture is:
at the same time, based on the mean value of the pore diameter
With the aperture standard deviation σ (r), the coefficient of variation of aperture cv (r) can be calculated, i.e.:
all the indexes can provide reference basis for establishing the permeability discrete element.
Step six, converting the aperture discrete element into a permeability discrete element: in a discrete element combination comprising 3 discrete elements, it is assumed that the permeability of each discrete element is in turn φ1、φ2、φ3Etc., in the unit mD. In order to ensure that the average permeability of the discrete element combination is consistent with the integral permeability of the model reservoir, the relation formula is satisfied:
meanwhile, in order to make the dispersion degree of the permeability discrete element substantially consistent with the dispersion degree of the pore size distribution, the permeability discrete element should also satisfy the formula:
in the formula, cv (phi) represents the permeability coefficient of variation in discrete element combinations, and is dimensionless. Wherein the standard deviation σ (φ) of the permeability dispersion element can be further expressed as:
the unit mD. In addition, N of target layer of cow hoof pond set in Yu southeast region2The adsorption-desorption curve belongs to H4Type, the corresponding pore system is of the single-sided slit type, and therefore the relationship is satisfied:
through six formulas in the simultaneous steps, the following can be solved:
namely, the permeability of each discrete unit in the discrete element combination is as follows in sequence: 0.00051mD, 0.00257mD, and 0.00463 mD.
Step seven, extrapolating the permeability discrete element to the whole simulation system: in general, the stratums in the research area are distributed horizontally, so that the discrete element combination can be expanded to the target layer of the cattle hoof pond group in the whole area A in a horizontal repeating mode and embedded into the whole discrete element model. The remaining formations can be uniformly characterized by uniform permeability.
Those skilled in the art will understand that the pore size distribution and the accurate measurement of permeability parameters are important prerequisites for the permeability discrete element simulation, and the representativeness and reliability of the actual sample can affect the accuracy of the numerical simulation at the later stage. Therefore, in order to ensure that the calculation result of the method can be effectively compared with the actual geological condition, a representative sample needs to be screened before numerical simulation, and the permeability numerical simulation result has higher precision.
Claims (5)
1. A permeability discrete element simulation method based on a pore system is characterized by comprising the following steps:
step 1, measuring the average permeability and a gas adsorption-desorption curve of a reservoir where a research object is located in a research area;
step 2, determining the type of pores according to the gas adsorption-desorption curve obtained in the step 1;
step 3, simplifying the pore types obtained in the step 2 to obtain a discretized pore size model;
step 4, calculating the basic statistical parameters of the pore size distribution of the discretization pore size model obtained in the step 3;
step 5, converting the discretization aperture module obtained in the step 3 into a permeability discrete element according to the basic statistical parameters of the aperture distribution of the discretization aperture model obtained in the step 4;
step 6, expanding and embedding the permeability discrete element obtained in the step 5 into a reservoir where the research object is located to obtain a permeability discrete element model of the reservoir where the research object is located in the research area;
in step 3, the specific method for converting the original aperture model into the discretized aperture model is as follows:
firstly, drawing an original aperture model according to the characteristics of different aperture models obtained in the step 2;
secondly, setting the total length of the original aperture model as d and unit nm; the original aperture model comprises n discrete element combination units, and the length corresponding to each discrete element combination unit is
Next, the average pore size r of the ith discrete element combination cell is calculated according toi：
Wherein S isiThe area actually covered by the aperture in the ith discrete unit;
finally, according to the aperture r of each discrete element combination unit obtained aboveiAnd splicing and drawing to obtain a discretized aperture model.
2. The method as claimed in claim 1, wherein in step 1, m samples of different positions and depths of the stratum where the object to be studied is located in the study area are collected, and the permeability of each sample is measured and recorded as k1、k2、k3……km；
Secondly, the formula (1) is used to calculate the mean permeability of the stratum in which the study object is located in the study area
3. The method for simulating the discrete element of permeability based on the pore system according to claim 1, wherein in the step 4, the specific method for calculating the basic statistical parameters of the pore size distribution of the discretized pore size model obtained in the step 3 is as follows:
setting the discrete element aperture model obtained in the step 2 to comprise n discrete element combination units, wherein the aperture in each discrete element combination unit is r1、r2、r3……rnIn nm, the main statistical parameters can be expressed as:
wherein the content of the first and second substances,
the mean value of the aperture of the discrete element aperture model is unit nm; σ (r) refers to the standard deviation of the aperture of the discrete element aperture model, in nm; cv (r) refers to the coefficient of variation of the discretized cellular aperture model.
4. The method for simulating the permeability discrete element based on the pore system according to claim 1, wherein in the step 5, the concrete method for converting the discretized pore size model combination obtained in the step 3 into the permeability discrete element model combination is as follows:
firstly, if a permeability discrete element model combination is set to include n' permeability discrete units, where n ═ 2n, then the permeability of each permeability discrete unit in the permeability discrete element model combination is sequentially expressed as
The unit mD;
wherein the average permeability of the permeability discrete element model combination
The following relationship should be satisfied:
wherein the content of the first and second substances,
the mean permeability of the stratum in which the study object is located in the study area;
the permeability variation coefficient of the permeability discrete element model combination
The following relationship should be satisfied:
wherein cv (r) refers to the coefficient of variation of the discrete element aperture model;
standard deviation of the permeability discrete element model combination
It is further expressed as:
secondly, complement specific conditional relationships according to different pore structures, wherein assuming that the discrete element combination contains 2n permeability discrete units, then:
if the pore system is open on both sides, the relationship should be satisfied:
if the pore system is an ink bottle, the relationship is satisfied:
if the pore system is of the parallel slit type, the relationship is satisfied:
if the pore system is of the single-sided slit type, the relationship is satisfied:
Assuming that the discrete element combination contains 2n +1 permeability discrete elements, then:
if the pore system is open on both sides, the relationship should be satisfied:
if the pore system is an ink bottle, the relationship is satisfied:
if the pore system is of the parallel slit type, the relationship is satisfied:
if the pore system is of the single-sided slit type, the relationship is satisfied:
Finally, through the simultaneous formulas (5) - (11), the permeability value corresponding to each discrete element combination unit in the discrete element combination is solved
5. The method according to claim 1, wherein in step 6, the permeability discrete element obtained in step 5 is expanded and embedded into the reservoir where the research object is located by adopting a horizontal repetition or longitudinal repetition mode.
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