Method for determining sand-shale effective reservoirs using petrophysical facies

Abstract

The present application provides a kind of method for determining effective reservoir of sandstone by rock physical phase, comprising: step 1: dividing rock physical phase by core observation;Step 2, the corresponding logging response characteristics of different rock physical phase are determined, preferably sensitive logging curve;Step 3: establish different rock physical phase porosity interpretation model of sandstone reservoir, and determine the lower limit standard of different rock physical phase effective reservoir porosity;Step 4: determine the effective reservoir of sandstone according to the lower limit standard of different rock physical phase effective reservoir.The method for determining effective reservoir of sandstone by rock physical phase can quickly and accurately classify and identify effective reservoir and non-effective reservoir of sandstone, solve the problem of effective reservoir identification of complex sandstone body, provide a basis for effective use of this type of reservoir, and have important guiding significance for the development practice of this type of reservoir.The effective reservoir identification method provided by the present application is simple, effective and fast, and is widely applicable.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of oil reservoir development, and particularly relates to a method for determining effective reservoirs of glutenite by using rock physical facies. BACKGROUND

[0002] Due to differences in paleostructural features, depositional paleogeomorphology, hydrodynamic conditions and genetic mechanisms, glutenite reservoirs have complex and variable lithology, great variation in parent rock composition and low maturity, which results in strong reservoir heterogeneity. Although FMI imaging logging and nuclear magnetic resonance logging data can be used to directly identify effective reservoirs, in actual exploration and development production processes, such data is expensive to obtain and difficult to collect in large quantities, which cannot be widely applied to practical work, and brings great difficulties to the development of glutenite reservoirs. Therefore, a conventional logging identification method for effective reservoirs of glutenite reservoirs needs to be established.

[0003] At present, many studies on the identification of effective reservoirs of glutenite have been carried out at home and abroad. Most of the methods adopt the method of taking reservoirs as the research object, using logging constrained inversion technology and time-frequency analysis technology to predict glutenite reservoirs, which has the defect of insufficient precision. Or the lithology is subdivided, and a conventional logging data identification mode is established. Due to different sedimentary environments, different lithology and different gravel composition in different regions, this method is not universal.

[0004] In the Chinese patent application with the application number CN201810141075.X, a conventional logging quantitative identification method for effective reservoirs of glutenite is disclosed, which comprises the following steps: step 1, correcting the environmental impact of logging data; step 2, determining the logging response characteristics of effective reservoirs and optimizing sensitive logging curves; step 3, calculating the reservoir identification parameter R; step 4, calculating the grain size indication parameter G; step 5, calculating the effective space parameter P; step 6, constructing the calculation model E of the reservoir effectiveness index; and step 7, combining the oil test situation to establish the quantitative division standard of effective reservoirs. The conventional logging quantitative identification method for effective reservoirs of glutenite fuses multiple conventional logging curves to establish a quantitative formula and division identification standard for effective reservoirs, improves the quantitative identification precision of effective reservoirs of glutenite, and provides an important reference for the division identification of effective reservoirs and the optimization of oil test intervals in complex glutenite reservoirs in the case of lack of imaging and nuclear magnetic logging data.

[0005] The Chinese patent application, application number CN202010450220.X, describes a computational method for evaluating the effectiveness of sandstone and conglomerate reservoirs using conventional well logging data. First, a fitting method is used to establish computational models for porosity and irreducible water saturation. Then, a volumetric model is used to calculate acoustic porosity and neutron porosity. Furthermore, based on the logging response characteristics of five pore throat types—shrinking, necking, lamellar, curved lamellar, and tubular—the porosity calculation formulas for each component are determined, enabling a detailed characterization of reservoir effectiveness. This inventive method, based on conventional well logging data, has been applied and promoted in multiple oil and gas fields, demonstrating good applicability.

[0006] Chinese patent application number CN201811008293.2 discloses a method for predicting effective conglomerate reservoirs based on well-constrained matching pursuit (MP). This method involves determining conglomerate thickness using a complex domain MCP algorithm. Furthermore, during amplitude calculation using MCP, well logging data is used as prior information to iteratively invert conglomerate porosity. The effective reservoir identification factor (pore thickness coefficient) is obtained by multiplying the conglomerate thickness and porosity, and effective reservoir prediction is performed in the work area. This MCP-based method obtains conglomerate thickness information using a MCP algorithm, then inverts conglomerate porosity using a well-constrained MCP algorithm. The weighted product of the two is then used to obtain the effective reservoir identification factor, improving the accuracy of conglomerate reservoir prediction.

[0007] Chinese patent application number CN202010802324.2 discloses a method for predicting the reservoir formations in conglomerate reservoirs, including the following steps: S1: Identifying reservoir formations in wells where oil has been tested or cored by analyzing the faulting activity and vertical distribution sequence characteristics of the conglomerate study area through core observation and well logging data. S2: Determining the relationship between the reservoir lithology, physical properties, electrical properties, and oil content of the reservoir, as well as electrical property identification criteria for the reservoir, and identifying effective reservoir formations in drilled wells based on the electrical property identification criteria. S3: Determining the lithologic sensitivity, reservoir sensitivity, and physical property sensitivity elastic parameters of the drilled conglomerate body. S4: Inferring the distribution of rock physical parameters at unknown locations in the underground space based on the elastic parameters using prestack seismic reflection characteristics. S5: Predicting the spatial distribution of porosity and permeability parameters based on the distribution of rock physical parameters, thereby predicting the distribution range of effective reservoirs. This method addresses the effectiveness of predicting the reservoir formations in conglomerate reservoirs and verifies the reliability of the method.

[0008] The above existing technologies are significantly different from the present invention and fail to solve the technical problem we want to solve. Therefore, we have invented a new method for determining effective sandstone reservoirs using rock physical phases. Summary of the Invention

[0009] The object of the present invention is to provide a method for determining effective conglomerate reservoirs by utilizing rock physical phases, which can quickly and accurately distinguish effective conglomerate reservoirs.

[0010] The object of the present invention can be achieved by the following technical measures: a method for determining an effective reservoir of sandstone and conglomerate using rock physical phases, the method for determining an effective reservoir of sandstone and conglomerate using rock physical phases comprising:

[0011] Step 1: Classify rock physical phases through core observation;

[0012] Step 2: Identify the logging response characteristics corresponding to different rock physics and select the sensitive logging curves;

[0013] Step 3: Establish porosity interpretation models for different rock physical phases in the sandstone conglomerate reservoir and determine the lower limit standards for effective reservoir porosity for different rock physical phases;

[0014] Step 4: Determine the effective sandstone reservoir based on the lower limit standards of effective reservoirs of different rock physical phases.

[0015] The purpose of the present invention can also be achieved by the following technical measures:

[0016] In step 1, the main lithology of the reservoir is divided into three rock physical phases through core observation: sandstone phase, gravelly sandstone phase, and conglomerate phase.

[0017] In step 1, the main lithologies of the reservoir include limy sandstone, conglomerate, coarse sandstone, fine sandstone, gravelly sandstone, siltstone, and gravelly fine sandstone. According to the oil-bearing characteristics, the coarse sandstone, fine sandstone, siltstone, and limy sandstone are classified as sandstone facies, the gravelly sandstone and gravelly fine sandstone are classified as gravelly sandstone facies, and the conglomerate is classified as conglomerate facies.

[0018] In step 2, sensitivity curves are optimized to distinguish different rock physical phases, including microelectrodes, acoustic transit time, resistivity, etc., and based on the logging response characteristics of reservoir sandstone phase, gravelly sandstone phase, and conglomerate phase, the logging influence ranges of acoustic transit time and resistivity of different rock physical phases are established to form an identification chart for different rock physical phases.

[0019] In step 3, based on the sandstone rock physical phase identification chart, the functional relationship between the porosity data of different rock physical phases and the acoustic wave time difference curve is established through core analysis:

[0020] Φ 砂岩相 =a1*△t+b1

[0021] Φ 砾状砂岩相 =a2*△t+b2

[0022] Φ 砾岩相 =a3*△t+b3

[0023] Where Φ is the porosity; △t is the acoustic time difference; a i , b i (i=1,2,3) are the unknown coefficients

[0024] In step 3, the core analysis data are used to regress the porosity interpretation model of different petrophysical phases.

[0025] In step 3, the lower limits of the physical properties of the effective reservoirs of the sandstone phase and the gravel sandstone phase are determined. The sandstone phase and the gravel sandstone phase have good physical properties. The effective reservoir porosity of the sandstone phase is greater than or equal to 15%, and the effective reservoir porosity of the gravel sandstone phase is greater than or equal to 12%. The oil properties are mainly characterized by oil spots, oil immersion, and oil-rich.

[0026] In step 3, it is determined that the conglomerate phase has poor physical properties, the effective reservoir porosity of the conglomerate phase is greater than or equal to 10%, and the oil properties are mainly characterized by oil spots, fluorescence, oil traces, and no oil.

[0027] In step 4, the reservoir is divided into effective reservoir and ineffective reservoir according to the size of the effective reservoir porosity curve value. Through core analysis data, it is judged that the sandstone phase with a porosity greater than or equal to 15% is an effective reservoir, the gravel sandstone phase with a porosity greater than or equal to 12% is an effective reservoir, and the conglomerate phase with a porosity greater than or equal to 10% is an effective reservoir.

[0028] The method of identifying effective conglomerate reservoirs using rock physical phases in the present invention classifies rock physical phases through core observation. Based on the characteristics of conventional logging curves of three different rock physical phases in conglomerate, the logging curves are optimized to identify the three rock physical phase parameters. A functional relationship between the logging curves and porosity of different rock physical phases is established with the logging response characteristic curve. A lower limit standard for determining the porosity values ​​of different rock physical phases in the effective conglomerate reservoir is established, thereby achieving the purpose of quantitatively identifying effective conglomerate reservoirs. This method of identifying effective conglomerate reservoirs using rock physical phases can quickly and accurately classify and identify effective and ineffective conglomerate reservoirs, solving the problem of identifying effective reservoirs in complex conglomerate bodies, providing a basis for the effective utilization of this type of oil reservoir, and having important guiding significance for the development practice of this type of oil reservoir. The effective reservoir identification method provided by the present invention is simple, effective, fast, and widely applicable. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 A flowchart of a specific embodiment of the method for determining an effective sandstone reservoir by utilizing rock physical phases according to the present invention;

[0030] Figure 2 is an electrical cross-plot of different rock physical phases in a specific embodiment of the present invention;

[0031] Figure 3This is a discriminant diagram of the lower limit of effective reservoir porosity of sandstone facies in a specific embodiment of the present invention;

[0032] Figure 4 This is a discriminant diagram of the lower limit of the effective reservoir porosity of the gravelly sandstone facies in a specific embodiment of the present invention;

[0033] Figure 5 This is a discriminant diagram of the lower limit of the effective reservoir porosity of the conglomerate facies in a specific embodiment of the present invention;

[0034] Figure 6 This is a diagram showing the quantitative identification results of effective reservoirs in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0035] It should be noted that the following detailed descriptions are exemplary and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which the present invention belongs.

[0036] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, they indicate the presence of features, steps, operations and / or combinations thereof.

[0037] The method of the present invention for determining effective sandstone reservoirs using rock physical phases specifically includes the following steps:

[0038] Step 1: Classify rock physical phases through core observation;

[0039] Step 2: Identify the logging response characteristics corresponding to different rock physics and select the sensitive logging curves;

[0040] Step 3: Establish porosity interpretation models for different rock physical phases in the sandstone conglomerate reservoir and determine the lower limit standards for effective reservoir porosity for different rock physical phases;

[0041] Step 4: Determine the effective sandstone reservoir based on the lower limit standards of effective reservoirs of different rock physical phases.

[0042] The following are several specific embodiments of the present invention.

[0043] Example 1

[0044] In a specific embodiment 1 of the present invention, Figure 1 As shown, Figure 1The flowchart of the method for determining effective sandstone reservoirs using rock physical phases of the present invention includes the following steps:

[0045] Step 101: Classify rock physical phases through core observation;

[0046] Core observations show that the reservoir's main lithologies include limy sandstone, conglomerate, coarse sandstone, fine sandstone, gravelly sandstone, siltstone, and gravelly fine sandstone. Based on their rock physical characteristics, the reservoir is divided into three rock physical facies: coarse sandstone, fine sandstone, siltstone, and limy sandstone are classified as sandstone facies, gravelly sandstone and gravelly fine sandstone are classified as gravelly sandstone facies, and conglomerate is classified as conglomerate facies.

[0047] Step 102: clarify the logging response characteristics corresponding to different rock physics and select sensitive logging curves;

[0048] The optimal sensitivity curves are used to distinguish different rock physical phases, including microelectrodes, acoustic transit time, resistivity, etc., and based on the logging response characteristics of reservoir sandstone phase, gravelly sandstone phase, and conglomerate phase, the logging influence ranges of acoustic transit time and resistivity of different rock physical phases are established to form identification charts for different rock physical phases.

[0049] Step 103: Establish porosity interpretation models for different rock physical phases in the sandstone reservoir and establish lower limit standards for the porosity of different rock physical phases in the effective reservoir; and regress the porosity interpretation models for different rock physical phases using core analysis data.

[0050] Step 104: determining the effective sandstone reservoir;

[0051] By combining core analysis data with the oil content of the core, the effective reservoirs of different rock physical phases can be determined at the oil spot and above oil content level.

[0052] The present invention's method for identifying effective conglomerate reservoirs using petrophysical facies can quickly and accurately classify and identify effective and ineffective conglomerate reservoirs. This method addresses the challenge of identifying effective reservoirs in complex conglomerate bodies, provides a foundation for the effective development of this type of reservoir, and offers significant guidance for practical development of this type of reservoir. The effective reservoir identification method provided by the present invention is simple, effective, rapid, and widely applicable.

[0053] Example 2

[0054] In a second specific embodiment of the present invention, the method for determining an effective conglomerate reservoir using rock physical phases includes:

[0055] Step 1: Classify rock physical phases through core observation;

[0056] Through core observation, the main reservoir lithologies: limy sandstone, conglomerate, coarse sandstone, fine sandstone, gravelly sandstone, siltstone, and gravelly fine sandstone are divided into three rock physical phases according to their oil-bearing characteristics: sandstone phase (coarse sandstone, fine sandstone, siltstone, limy sandstone), gravelly sandstone phase (gravelly sandstone, gravelly fine sandstone), and conglomerate phase.

[0057] Step 2: Clarify the logging response characteristics corresponding to different rock electrical parameters and select the sensitive logging curves;

[0058] Microelectrode, acoustic transit time, and resistivity curves were identified as sensitive curves. Based on the logging response characteristics of the reservoir sandstone, gravelly sandstone, and conglomerate facies, a crossplot of acoustic transit time and resistivity curves was established, forming an identification chart for the reservoir sandstone, gravelly sandstone, and conglomerate facies.

[0059] It is determined that the acoustic wave time difference value of the sandstone phase is greater than 340μs / m, and the resistivity is 10-20Ω.m; the acoustic wave time difference value of the gravel sandstone phase is 340-400μs / m, and the resistivity is greater than or equal to 20Ω.m; the acoustic wave time difference value of the conglomerate phase is less than 340μs / m, and the resistivity is greater than 30Ω.m.

[0060] Based on the reservoir rock physical phase identification chart, the relationship between the porosity data obtained from the core analysis test data and the acoustic wave transit time curve is established, and the functional relationship of different rock physical phases is regressed as follows:

[0061] Φ 砂岩相 =a1*△t+b1

[0062] Φ 砾状砂岩相 =a2*△t+b2

[0063] Φ 砾岩相 =a3*△t+b3

[0064] Where Φ is the porosity; △t is the acoustic time difference; a i , b i (i=1,2,3) are unknown coefficients.

[0065] Step 3: Establish porosity interpretation models for different rock physical phases in the sandstone conglomerate reservoir and establish lower limit standards for the porosity of different rock physical phases in the effective reservoir; use core analysis and laboratory data to regress the porosity interpretation models for different rock physical phases.

[0066] Step 4: Determine the effective sandstone reservoir;

[0067] Core analysis data show that sandstone facies with a porosity greater than or equal to 15% are effective reservoirs, gravelly sandstone facies with a porosity greater than or equal to 12% are effective reservoirs, and conglomerate facies with a porosity greater than or equal to 10% are effective reservoirs.

[0068] Example 3

[0069] In a specific embodiment 3 of the present invention, the method for determining an effective sandstone reservoir using rock physical phases includes:

[0070] In step 1, based on core observation and rock thin section identification, various lithologies are divided into three rock physical phases. Based on the logging response characteristics of various rock physical phases in the reservoir, the intersection diagram of acoustic wave time difference and resistivity curve is established to form the identification chart of each rock physical phase in the reservoir, such as Figure 2 shown.

[0071] In step 2, based on the reservoir rock physical phase identification chart, the relationship between the porosity data obtained through core analysis test data and the acoustic wave transit time curve is established, and the functional relationship between different rock physical phases is regressed as follows:

[0072] Φ 砂岩相 =0.133*△t-17.156

[0073] Φ 砾状砂岩相 =(△t-156) / 8.52

[0074] Φ 砾岩相 =(△t-218) / 9.834

[0075] Where Φ is the porosity; △t is the acoustic time difference;

[0076] In step 3, the effective reservoir oil content of the three petrophysical phases is determined to be oil spots and above. The sandstone phase and gravel sandstone phase have good physical properties. The lower limits of the effective reservoir physical properties are: the effective reservoir porosity of the sandstone phase is greater than or equal to 15%, and the effective reservoir porosity of the gravel sandstone phase is greater than or equal to 12%. The conglomerate phase has poor physical properties, and the effective reservoir porosity of the conglomerate phase is greater than or equal to 10%. Figure 3-5 shown.

[0077] In step 4, the reservoir is divided into effective reservoir and non-effective reservoir according to the value of the effective reservoir porosity curve. Specifically, the effective reservoir porosity of the sandstone phase is greater than or equal to 15%, the effective reservoir porosity of the gravel sandstone phase is greater than or equal to 12%, and the effective reservoir porosity of the conglomerate phase is greater than or equal to 10%. Figure 6 shown.

[0078] The present invention has the following advantages: It uses well logging curves to establish relationships between different petrophysical facies and logging curves, and uses core analysis data and acoustic transit time curves to determine the porosity of different petrophysical facies. Reservoir effectiveness is determined by the oil-bearing grades corresponding to the porosity distribution ranges of different petrophysical facies. This allows for rapid and accurate classification and identification of effective and ineffective reservoirs, avoiding the many uncertainties associated with identifying effective reservoirs due to complex lithology. The effective reservoir identification method provided by the present invention is simple, effective, rapid, and widely applicable.

[0079] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art may modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features therein. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

[0080] Except for the technical features described in the specification, all other technical features are known technologies to those skilled in the art.

Claims

1. A method for determining effective sandstone reservoirs using rock physical phases, characterized in that: The method for determining effective sandstone reservoirs using rock physical phases includes: Step 1: Classify rock physical phases through core observation; Step 2: Identify the logging response characteristics corresponding to different rock physics and select sensitive logging curves; Step 3: Establish porosity interpretation models for different rock physical phases in the sandstone conglomerate reservoir and determine the lower limit standards for effective reservoir porosity for different rock physical phases; Step 4: Determine the effective reservoir of sandstone and conglomerate based on the lower limit standards of effective reservoirs of different rock physical phases; In step 1, the main lithology of the reservoir is divided into three types of rock physical phases based on rock physical characteristics through core observation. The main lithology of the reservoir includes limy sandstone, conglomerate, coarse sandstone, fine sandstone, gravelly sandstone, siltstone, and gravelly fine sandstone. Based on the oil-bearing characteristics, the coarse sandstone, fine sandstone, siltstone, and limy sandstone are classified as sandstone phase, the gravelly sandstone and gravelly fine sandstone are classified as gravelly sandstone phase, and the conglomerate is classified as conglomerate phase. In step 2, sensitive curves are selected to distinguish different rock physical phases, including microelectrode, acoustic transit time and resistivity curves. Based on the logging response characteristics of the reservoir sandstone phase, gravelly sandstone phase and conglomerate phase, a cross-plot of acoustic transit time curves and resistivity curves is established to form an identification chart for the reservoir sandstone phase, gravelly sandstone phase and conglomerate phase. In step 3, the porosity interpretation model of different rock physical phases is regressed using core analysis and laboratory data; Determine the lower limits of the physical properties of effective reservoirs in sandstone and gravel sandstone facies. Sandstone and gravel sandstone facies have good physical properties. The effective reservoir porosity of sandstone facies is ≥15%, and the effective reservoir porosity of gravel sandstone facies is ≥12%. The oil properties are mainly characterized by oil spots, oil immersion, and oil-rich. In step 4, the reservoir is divided into effective reservoir and ineffective reservoir according to the value of the effective reservoir porosity curve. According to the core analysis data, the sandstone phase with a porosity of ≥15% is an effective reservoir, the gravel sandstone phase with a porosity of ≥12% is an effective reservoir, and the conglomerate phase with a porosity of ≥10% is an effective reservoir.

2. The method for determining effective sandstone reservoirs using rock physical phases according to claim 1, characterized in that: In step 2, it is determined that the acoustic wave delay value of the sandstone phase is greater than 340 μs / m and the resistivity is 10-20 Ω.m; the acoustic wave delay value of the gravel sandstone phase is 340-400 μs / m and the resistivity is ≥20 Ω.m; and the acoustic wave delay value of the conglomerate phase is less than 340 μs / m and the resistivity is greater than 30 Ω.m.

3. The method for determining effective sandstone reservoirs using rock physical phases according to claim 1, characterized in that: In step 2, based on the reservoir rock physical phase identification chart, the relationship between the porosity data of different rock physical phases and the acoustic wave time difference curve is established through core analysis: Φ 砂岩相 =a1*△t+b1 Φ 砾状砂岩相 = a2*△t+b2 F 砾岩相 = a3*△t+b3 Where Φ is the porosity; △t is the acoustic time difference; a i , b i , i=1,2,3 are unknown coefficients.

4. The method for determining effective sandstone reservoirs using rock physical phases according to claim 1, characterized in that: In step 3, it is determined that the conglomerate phase has poor physical properties, the effective reservoir porosity of the conglomerate phase is ≥10%, and the oil properties are mainly characterized by oil spots, fluorescence, oil traces, and no oil.

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