Prediction method for high-quality reservoir of deeply-buried matrix type tight sandstone

Abstract

The invention discloses a method for predicting a high-quality reservoir of deep-buried matrix type tight sandstone. The method comprises the following steps: acquiring production data and reservoir physical property parameters of a target work area; drawing a porosity cumulative frequency and cumulative probability distribution diagram and a permeability cumulative frequency and cumulative probability distribution diagram according to the production data and the reservoir physical property parameters; respectively determining a porosity inflection point, a first permeability inflection point and a second permeability inflection point according to the porosity cumulative frequency and cumulative probability distribution diagram and the permeability cumulative frequency and cumulative probability distribution diagram; selecting a plurality of samples of the target work area, and determining a permeability upper limit point according to the plurality of samples; according to the porosity inflection point, the first permeability inflection point, the second permeability inflection point and the permeability upper limit point, reservoir types are divided, and a high-quality reservoir is determined. The method not only provides scientific basis for tight sandstone gas prediction, but also provides theoretical guidance for exploration and development of tight sandstone gas with similar geological backgrounds, and has important practical value for exploration and development of deep-layer and ultra-deep-layer tight sandstone gas.

Description

Technical Field

[0001] The invention relates to a prediction method for a deep-buried matrix-type dense sandstone high-quality reservoir, belonging to the technical field of oil and gas field geological exploration. Background Art

[0002] Deeply buried matrix-type tight sandstone reservoirs are dominated by microfractures, lacking distinct natural fracture systems. Their diagenetic heterogeneity is strong, and the genesis of high-quality reservoirs is controlled by multiple factors, making exploration challenging. However, their rich unconventional oil and gas resources have become a cutting-edge scientific issue in oil and gas geology. Early exploration efforts focused primarily on the vicinity of structural traps. In contrast, matrix-type reservoirs harbor abundant tight gas resources, but their thick sand bodies contain sedimentary interlayers that affect the seepage mechanism of diagenetic fluids. Furthermore, the distinct distribution of chlorite contributes to the strong diagenetic heterogeneity of the reservoirs and the complex mechanisms of high-quality reservoir formation. Consequently, accurate prediction of high-quality reservoirs is difficult. Summary of the Invention

[0003] In view of the above problems, the present invention mainly overcomes the shortcomings of the existing technology and proposes a prediction method for deep-buried matrix-type tight sandstone high-quality reservoirs.

[0004] The present invention solves the above technical problems and provides a technical solution: a method for predicting deep-buried matrix-type tight sandstone high-quality reservoirs, comprising the following steps: Step S10: Obtaining production data and reservoir physical property parameters of the target work area; Step S20: plotting a porosity cumulative frequency and cumulative probability distribution diagram and a permeability cumulative frequency and cumulative probability distribution diagram based on production data and reservoir physical property parameters; Step S30, determining the porosity inflection point, the first permeability inflection point, and the second permeability inflection point respectively according to the porosity cumulative frequency, cumulative probability distribution diagram, and the permeability cumulative frequency, cumulative probability distribution diagram; Step S40: Select several samples from the target work area and determine the upper limit of permeability based on the samples; Step 50: Classify reservoir types according to the porosity inflection point, the first permeability inflection point, the second permeability inflection point, and the upper permeability limit point, and determine high-quality reservoirs.

[0005] A further technical solution is that the reservoir physical property parameters include porosity and permeability.

[0006] A further technical solution is that the specific steps of step S30 are: Step S31, fitting a porosity probability curve and a permeability probability curve in the porosity cumulative frequency and cumulative probability distribution graph and the permeability cumulative frequency and cumulative probability distribution graph respectively; Step S32: Determine the porosity inflection point, the first permeability inflection point, and the second permeability inflection point according to the porosity probability curve and the permeability probability curve.

[0007] A further technical solution is to obtain the permeability of each sample in step S40, draw a permeability distribution histogram, and determine the permeability upper limit point based on the permeability distribution histogram.

[0008] A further technical solution is that the point in the permeability distribution histogram with a cumulative frequency greater than 95% is the permeability upper limit point.

[0009] A further technical solution is that the reservoir types include Type I primary / secondary pore-microfracture reservoir, Type II secondary pore-microfracture reservoir, Type III primary / secondary pore reservoir, and Type IV secondary pore reservoir.

[0010] A further technical solution is that the Type I primary / secondary pore-microfracture reservoir and Type III primary / secondary pore reservoir are high-quality reservoirs.

[0011] A further technical solution is that the specific classification criteria in step S50 are: When the porosity is greater than the porosity inflection point and the permeability is between the second inflection point of permeability and the upper limit of permeability, the reservoir is a Type I primary / secondary pore-microfracture reservoir; When the porosity is less than or equal to the porosity inflection point and the permeability is between the second inflection point of permeability and the upper limit of permeability, the reservoir is a type II secondary pore-microfracture reservoir; When the porosity is greater than the porosity inflection point and the permeability is between the first inflection point and the second inflection point of permeability, the reservoir is a Type III primary / secondary porosity reservoir; When the porosity is less than or equal to the porosity inflection point and the permeability is greater than the second inflection point of permeability or less than the first inflection point of permeability, the reservoir is a Type IV secondary porosity reservoir.

[0012] Beneficial effects of the present invention: According to the relationship between reservoir physical properties and production capacity and the distribution characteristics of reservoir physical properties, the present invention divides the reservoirs in the study area into relatively high-quality micro-fracture-dominated type Type I primary / secondary pore-micro-fracture reservoirs, Type II secondary pore-micro-fracture reservoirs, Type III primary / secondary pore reservoirs, and Type IV secondary pore reservoirs; the present invention not only provides a scientific basis for the prediction of the "sweet spots" of tight sandstone gas, but also provides theoretical guidance for the exploration and development of tight sandstone gas in similar geological backgrounds, and has important practical value for the exploration and development of deep-ultra-deep tight sandstone gas. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 is the cumulative frequency and cumulative probability distribution diagram of porosity; Figure 2 is the cumulative frequency and cumulative probability distribution diagram of permeability; Figure 3 is the permeability distribution histogram. DETAILED DESCRIPTION

[0014] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only part of the embodiments of the invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0015] The present invention provides a method for predicting a deep-buried matrix-type tight sandstone high-quality reservoir, comprising the following steps: Step S10: Obtain production data and reservoir physical properties (porosity and permeability) of more than 30 wells in the target work area; Step S20: Draw a porosity cumulative frequency and cumulative probability distribution diagram based on production data and reservoir physical parameters (e.g. Figure 1 As shown) and the cumulative frequency and cumulative probability distribution of permeability (as shown Figure 2 shown); Step S30, determining the porosity inflection point, the first permeability inflection point, and the second permeability inflection point respectively according to the porosity cumulative frequency, cumulative probability distribution diagram, and the permeability cumulative frequency, cumulative probability distribution diagram; Step S31, fitting a porosity probability curve and a permeability probability curve in the porosity cumulative frequency and cumulative probability distribution graph and the permeability cumulative frequency and cumulative probability distribution graph respectively; Step S32: determining the porosity inflection point (2.4%), the first permeability inflection point (0.02 mD), and the second permeability inflection point (0.5 mD) according to the porosity probability curve and the permeability probability curve; Step S40: Select several samples from the target work area and determine the upper limit of permeability based on the samples; The permeability of each sample is obtained, and a permeability distribution histogram is drawn (e.g. Figure 3 As shown in the figure), the upper limit of permeability is determined based on the permeability distribution histogram; Specifically, six permeability data ranges are defined: 0.001-0.1mD, 0.01-0.1mD, 0.1-1mD, 1-10mD, and 10-100mD; Then, the corresponding permeability probability within each permeability data range is counted, and then a permeability distribution histogram is drawn; Finally, starting from the first range, the cumulative probability of permeability of each range is superimposed, and the maximum value of the permeability data range corresponding to the cumulative probability of permeability greater than 95% is taken as the upper limit of permeability; that is, Figure 3 As shown in , the permeability cumulative probability is greater than 95% and the corresponding permeability data range is 1-10mD, so the upper limit of the permeability of the target work area is 10mD; Step 50: Classify the reservoir type (Type I primary / secondary pore-microfracture reservoir, Type II secondary pore-microfracture reservoir, Type III primary / secondary pore reservoir, Type IV secondary pore reservoir) based on the porosity inflection point, the first permeability inflection point, the second permeability inflection point, and the upper permeability limit, and determine the high-quality reservoir (Type I primary / secondary pore-microfracture reservoir, Type III primary / secondary pore reservoir). If the permeability is between the second inflection point and the upper limit of permeability, the reservoir is a Type I primary / secondary pore-microfracture reservoir; When the porosity is less than or equal to the porosity inflection point and the permeability is between the second inflection point of permeability and the upper limit of permeability, the reservoir is a type II secondary pore-microfracture reservoir; When the porosity is greater than the porosity inflection point and the permeability is between the first inflection point and the second inflection point of permeability, the reservoir is a Type III primary / secondary porosity reservoir; When the porosity is less than or equal to the porosity inflection point and the permeability is greater than the second inflection point of permeability or less than the first inflection point of permeability, the reservoir is a Type IV secondary porosity reservoir.

[0016] The above description does not limit the present invention in any form. Although the present invention has been disclosed through the above embodiments, it is not intended to limit the present invention. Any technician familiar with the profession can use the technical content disclosed above to make some changes or modifications to equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are within the scope of the technical solution of the present invention.

Claims

1. A method for predicting high-quality deep-buried matrix-type tight sandstone reservoirs, characterized in that: The following steps are involved: Step S10: Obtaining production data and reservoir physical property parameters of the target work area; Step S20: plotting a porosity cumulative frequency and cumulative probability distribution diagram and a permeability cumulative frequency and cumulative probability distribution diagram based on production data and reservoir physical property parameters; Step S30, determining the porosity inflection point, the first permeability inflection point, and the second permeability inflection point respectively according to the porosity cumulative frequency, cumulative probability distribution diagram, and the permeability cumulative frequency, cumulative probability distribution diagram; Step S40: Select several samples from the target work area and determine the upper limit of permeability based on the samples; Step 50: Classify reservoir types according to the porosity inflection point, the first permeability inflection point, the second permeability inflection point, and the upper permeability limit point, and determine high-quality reservoirs.

2. The method for predicting a deep-buried matrix-type tight sandstone high-quality reservoir according to claim 1, characterized in that: The reservoir physical property parameters include porosity and permeability.

3. The method for predicting a deep-buried matrix-type tight sandstone high-quality reservoir according to claim 1, characterized in that: The specific steps of step S30 are: Step S31, fitting a porosity probability curve and a permeability probability curve in the porosity cumulative frequency and cumulative probability distribution graph and the permeability cumulative frequency and cumulative probability distribution graph respectively; Step S32: Determine the porosity inflection point, the first permeability inflection point, and the second permeability inflection point according to the porosity probability curve and the permeability probability curve.

4. The method for predicting a deep-buried matrix-type tight sandstone high-quality reservoir according to claim 1, characterized in that: In step S40 , the permeability of each sample is obtained, and a permeability distribution histogram is drawn, and the upper limit of the permeability is determined according to the permeability distribution histogram.

5. The method for predicting a deep-buried matrix-type tight sandstone high-quality reservoir according to claim 4, characterized in that: The point in the permeability distribution histogram with a cumulative frequency greater than 95% is the upper limit of the permeability.

6. The method for predicting a deep-buried matrix-type tight sandstone high-quality reservoir according to claim 1, characterized in that: The reservoir types include Type I primary / secondary pore-microfracture reservoir, Type II secondary pore-microfracture reservoir, Type III primary / secondary pore reservoir, and Type IV secondary pore reservoir.

7. The method for predicting a deep-buried matrix-type tight sandstone high-quality reservoir according to claim 6, characterized in that: The Type I primary / secondary pore-microfracture reservoir and Type III primary / secondary pore reservoir are high-quality reservoirs.

8. The method for predicting a deep-buried matrix-type tight sandstone high-quality reservoir according to claim 6, characterized in that: The specific classification criteria in step S50 are: When the porosity is greater than the porosity inflection point and the permeability is between the second inflection point of permeability and the upper limit of permeability, the reservoir is a Type I primary / secondary pore-microfracture reservoir; When the porosity is less than or equal to the porosity inflection point and the permeability is between the second inflection point of permeability and the upper limit of permeability, the reservoir is a type II secondary pore-microfracture reservoir; When the porosity is greater than the porosity inflection point and the permeability is between the first inflection point and the second inflection point of permeability, the reservoir is a Type III primary / secondary porosity reservoir; When the porosity is less than or equal to the porosity inflection point and the permeability is greater than the second inflection point of permeability or less than the first inflection point of permeability, the reservoir is a Type IV secondary porosity reservoir.

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