Method and device for determining relationship between sedimentary microfacies and oil and gas reservoir reserves

Abstract

The invention discloses a method and device for determining the relation between sedimentary microfacies and oil and gas reservoir reserves, and relates to the field of fine geological research of clastic rock oil and gas reservoir reserves. Determining the type of the sedimentary microfacies, and then utilizing a statistical method and regression analysis to demonstrate the relationship between the width of a river channel, the thickness of a sand body, the sand-to-ground ratio, the porosity, the permeability and the net gross ratio and the oil-gas content, so as to define the favorable sedimentary microfacies and residual oil-gas evaluation potential direction; and a reference basis is provided for oil and gas reservoir reserve engineering designs such as oil and gas reservoir productivity construction well patterns, well spacing and well types. In the clastic rock oil and gas reservoir reserve prediction method in the same type of sedimentary environment, the method has wide application and popularization prospects.

Description

Technical Field

[0001] The present invention relates to the field of fine geological research on clastic rock oil and gas reservoir reserves, and more particularly to a method and device for determining the relationship between sedimentary microfacies and oil and gas reservoir reserves. Background Art

[0002] Braided river deltas are deltas rich in fine-grained sandstone formed when braided rivers protrude into the sea or lake. These deltas offer superior sedimentary environments and abundant sediment supplies, and are susceptible to structural and fault influences, forming complex structural traps and fault zones. These areas are highly conducive to oil and gas accumulation. Currently, there have been several successful oil and gas exploration and development cases in braided river deltas, demonstrating their rich oil and gas resources and significant potential for exploration and development.

[0003] The formation of oil and gas reservoirs in braided river deltas is influenced by many factors, such as complex and diverse sediment sources, complex sedimentary environments formed by the combined effects of seas, rivers, and lakes, tectonic activities, and geological influences. As a result, the reservoir parameters of braided river deltas vary widely and are highly heterogeneous. The prediction of oil and gas exploration indicators such as sand body morphology, physical properties, and oil and gas content is difficult, and sedimentary microfacies analysis is needed to improve the accuracy of reserve prediction.

[0004] Traditional sedimentary microfacies analysis is typically based on extensive manual identification using well logging and seismic data, often based on the personal experience of geologists. This results in poor repeatability, low efficiency, and difficulty objectively characterizing sedimentary microfacies. The accuracy of well logging data is closely related to the accuracy of the logging instruments. Even after correction, logging data from wellbore collapse can still produce errors. Furthermore, inter-well logging data requires standardization, which further increases errors. Seismic data is affected by the quality of three-dimensional data. Due to the complex lithology and physical properties of low-porosity and ultra-low permeability reservoirs, seismic data can exhibit discontinuous seismic reflection phases, low correlation between attributes and drilled sand bodies, and difficulty identifying and accurately characterizing thin sand bodies. Consequently, the use of well logging and seismic data for sedimentary microfacies analysis has certain limitations and is difficult to meet the requirements of oil and gas field development.

[0005] Based on the above reasons, the present invention uses statistical methods to determine the well logging characteristics, core grain size and heavy mineral characteristics, sand body thickness, and sand-to-ground ratio of each sedimentary microfacies as the judgment criteria for sedimentary microfacies. Using core data, this method reduces the impact of well logging data errors on sedimentary microfacies judgment. Based on this, a reserve prediction model based on sedimentary parameters for different sedimentary microfacies is established through regression analysis, thereby improving the accuracy of reserve prediction. Summary of the Invention

[0006] To achieve the above object, the present invention provides the following technical solution: a method for determining the relationship between sedimentary microfacies and oil and gas reservoir reserves, comprising the following steps:

[0007] S1. Given a unit area z, different sedimentary microfacies are selected, and multiple research points are outlined under each sedimentary microfacies. The area of each research point is equal to the unit area. For each sedimentary microfacies, well logging data and core data of all its research points are obtained. The well logging data includes spontaneous potential logging curves, and the logging curve characteristics, core grain size and heavy mineral characteristics, sand body thickness and sand-to-shale ratio characteristics of each sedimentary microfacies are statistically analyzed.

[0008] S2. Obtain the hydrocarbon reservoir reserves and sedimentary microfacies parameters of each research point. The sedimentary microfacies parameters are numerical values, which are any one of channel width, sand body thickness, sand-to-shale ratio, porosity, permeability, and net-to-gross ratio.

[0009] S3. For each sedimentary microfacies, based on the data of all its research points, with the hydrocarbon reservoir reserves as the dependent variable y and the sedimentary microfacies parameters as the independent variable x, the function model of each sedimentary microfacies is respectively fitted.

[0010] S4. Match the well logging data and core data of the area to be studied with the logging curve characteristics, core grain size and heavy mineral characteristics, sand body thickness and sand-to-shale ratio characteristics of each sedimentary microfacies to determine the sedimentary microfacies of the area to be studied; obtain the area Z and sedimentary microfacies parameters X of the area to be studied.

[0011] S5. Based on the sedimentary microfacies of the area to be studied, substitute the sedimentary microfacies parameter X into the function model of the corresponding sedimentary microfacies to calculate the unit hydrocarbon reservoir reserve Y' of the area to be studied. The hydrocarbon reservoir reserve Y of the area to be studied is calculated by the following formula:

[0012]

[0013] The present invention is further configured as: further including S6. Calculate the single-well controlled reserve by the material balance method, and determine the economic limit well spacing by the economic model. The calculation formulas are as follows:

[0014]

[0015]

[0016] Among them, S is the total cost of single-well drilling and oil construction, in ten thousand yuan / well. p is the average annual gas production operation cost per well, in ten thousand yuan / well / year. A is the economic evaluation price of oil and gas, in yuan / m 3 . S, p, and A are obtained by query. E is the recovery factor of the hydrocarbon reservoir, in %, which is the single-well recovery factor of the same sedimentary microfacies. t is the stable production period of the area to be studied, in years, and t is the quotient of Y divided by the single-well annual production of the same sedimentary microfacies. d is the economic limit well spacing, in m. G sg is the single-well controlled reserve, 10 8 m 3. B is the proven gas-bearing area of the area to be studied, km 2 , obtained by analyzing the rock samples and logging curves of the area to be studied. Y is the oil and gas reservoir reserves of the area to be studied, 10 8 m 3 .

[0017] The present invention is further configured as: the sedimentary microfacies parameter is the sand-to-shale ratio or the sand body thickness, and the function model between the sedimentary microfacies parameter and the oil and gas reservoir reserves under each sedimentary microfacies is as follows:

[0018] y = ax 2 + bx + c

[0019] Wherein, y is the oil and gas reservoir reserves. x is the sand-to-shale ratio or the sand body thickness. a, b, and c are all constants, obtained by fitting based on the data of the research points, and each sedimentary microfacies has its corresponding a, b, and c.

[0020] The present invention is further configured as: the sedimentary microfacies include subaqueous distributary channel microfacies, channel margin microfacies, mouth bar microfacies, distal bar microfacies, sheet sand microfacies, subaqueous distributary channel interdistributary microfacies, shore-shallow lake mud microfacies.

[0021] The present invention is further configured as: when the sedimentary microfacies parameter is the sand body thickness and the sedimentary microfacies is the subaqueous distributary channel microfacies, the function model between the sand body thickness and the oil and gas reservoir reserves is:

[0022] y = 0.0368x 2 -0.187x + 0.2353

[0023] Wherein, the unit of y is 10 8 m 3 , and the unit of x is m.

[0024] The present invention is further configured as: when the sedimentary microfacies parameter is the sand body thickness and the sedimentary microfacies is the channel margin microfacies, the function model between the sand body thickness and the oil and gas reservoir reserves is:

[0025] y = 0.0534x 2 -0.2878x + 0.4349

[0026] Wherein, the unit of y is 10 8 m 3 , and the unit of x is m.

[0027] The present invention is further configured as: when the sedimentary microfacies parameter is the sand body thickness and the sedimentary microfacies is the sheet sand microfacies or the distal bar microfacies or the mouth bar microfacies, the function model between the sand body thickness and the oil and gas reservoir reserves is:

[0028] y = 0.0095x 2 -0.0066x - 0.0035

[0029] Among them, the unit of y is 10 8 m 3 , and the unit of x is m.

[0030] The present invention is further configured such that: the square of the correlation R of the function model between the sedimentary microfacies parameters and the hydrocarbon reservoir reserves under each sedimentary microfacies 2 is greater than 0.95.

[0031] The present invention is further configured such that: the logging data includes spontaneous potential logging curves. The characteristics of the logging curves include curve amplitude, curve shape, contact relationship, smoothness, tooth midline, thickness, and rhythm.

[0032] The present invention is further configured such that: the logging data further includes natural gamma logging curves. When analyzing sedimentary microfacies based on the logging data, the spontaneous potential logging curves are mainly used, and the natural gamma logging curves are used as supplements.

[0033] The present invention is further configured such that: the core grain size and heavy mineral characteristics include average grain size, heavy mineral characteristics, and C-M diagram.

[0034] The present invention is further configured such that: the heavy mineral characteristics include the average value of the ZTR index and the heavy mineral stability coefficient.

[0035] The present invention is further configured such that: the characteristics of the C-M diagram include the shape and trend of the suspension load curve.

[0036] The present invention is further configured such that: the core grain size and heavy mineral characteristics further include lithology, color, bedding structure, sorting, roundness, and oil and gas bearing property.

[0037] The present invention is further configured such that: the sorting is reflected by the grain size probability curve, and the elements of the grain size probability curve include component types, the overall fine cut-off point of two component types, the most developed component type, and the inclination of the straight line segment. Among them, the component types include rolling components, suspension components, and jumping components, and at least two component types are included in the core.

[0038] The present invention also provides a device for determining the relationship between sedimentary microfacies and hydrocarbon reservoir reserves, which includes a storage medium and a processor, and a computer program is stored on the storage medium. The processor is used to implement the method for determining the relationship between sedimentary microfacies and hydrocarbon reservoir reserves as described above when executing the computer program.

[0039] In summary, the present invention has the following beneficial effects compared with the prior art: Through well logging data and indoor core test data, the present invention qualitatively and quantitatively judges the characteristics of the sedimentary environment, combines the sand body thickness and sand-to-shale ratio to delineate, determines the types of sedimentary microfacies, and then uses statistical methods to demonstrate the relationship between different sedimentary microfacies and hydrocarbon-bearing properties, clarifies the favorable sedimentary microfacies and the evaluation potential direction of remaining oil and gas, and provides a reference basis for the reservoir reserve engineering design such as well pattern, well spacing, and well type for the production capacity construction of the oil and gas reservoir. Among the methods for predicting the reserves of clastic rock oil and gas reservoirs in the same type of sedimentary environment, this method has a broad application and promotion prospect. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a flow chart of the method for determining the relationship between sedimentary microfacies and oil and gas reservoir reserves in Example 1.

[0041] Figure 2 It is the well logging curve characteristics of each sedimentary microfacies in Example 2.

[0042] Figure 3 It is the C-M diagram of a certain area in Example 2.

[0043] Figure 4 It is the grain size probability diagram of a certain area in Example 2.

[0044] Figure 5 It is the small layer plane contour map of sand body thickness in a certain area in Example 2.

[0045] Figure 6 It is the small layer plane contour map of sand-to-shale ratio in a certain area in Example 2.

[0046] Figure 7 It is the characteristics related to the plane distribution pattern of sand body and the profile sedimentary evolution of each sedimentary microfacies in Example 2.

[0047] Figure 8 It is the sedimentary microfacies distribution map of a certain area in Example 2.

[0048] Figure 9 It is the linear relationship between the rectangular area representing the channel width and the sand body thickness in Example 2.

[0049] Figure 10 It is the function model of the underwater distributary channel microfacies in Example 2.

[0050] Figure 11 It is the function model of the channel margin microfacies in Example 2.

[0051] Figure 12 It is the function model of the sheet sand microfacies, distal bar microfacies, and mouth bar microfacies in Example 2. DETAILED DESCRIPTION OF THE INVENTION

[0052] The technical solution of the present invention will be clearly described below in conjunction with the accompanying drawings. Obviously, the described embodiments are not all embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the invention.

[0053] It should be noted that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "horizontal", "left", "right", "front", "rear", "transverse", "longitudinal", etc. is based on the orientation or positional relationship shown in the accompanying drawings. It is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0054] Embodiment 1

[0055] As Figure 1 shown, this embodiment provides a method for determining the relationship between sedimentary microfacies and hydrocarbon reservoir reserves, which includes the following steps:

[0056] S1. Given a unit area z, different sedimentary microfacies are selected. Under each sedimentary microfacies, a plurality of research points are outlined, and the area of each research point is equal to the unit area. For each sedimentary microfacies, the logging data and core data of all its research points are obtained, and the logging curve characteristics, core grain size and heavy mineral characteristics, sand body thickness and sand-to-shale ratio characteristics of each sedimentary microfacies are statistically analyzed.

[0057] The logging data includes spontaneous potential logging curves. The logging curve characteristics include curve amplitude, curve shape, contact relationship, smoothness, tooth midline, thickness, and rhythmicity. The curve amplitude is the overall amplitude of the logging curve, the curve shape is the shape of the logging curve, the contact relationship is the contact situation of the logging curve with the vertical direction at the bottom of the formation, the smoothness is the fluctuation frequency and amplitude of the logging curve; the tooth midline is the inclination degree of the midline of the tooth-shaped undulation; the thickness is the distance between the midlines of two adjacent tooth-shaped undulations; the rhythmicity is the regularity of the tooth-shaped undulations in the logging curve.

[0058] The core grain size and heavy mineral characteristics are obtained based on the observation and analysis of a large number of cores on site, including characteristics such as average grain size, heavy mineral characteristics, C-M diagram, etc. for judging the sedimentary environment. The core grain size and heavy mineral characteristics also include characteristics such as lithology, color, bedding structure, sorting, roundness, and oil and gas bearing property for judging the paleo-sedimentary environment and hydrodynamic conditions. The heavy mineral characteristics include the average value of the ZTR index and the heavy mineral stability coefficient. The characteristics of the C-M diagram include the shape and trend of the suspension load curve. The sorting is reflected by the grain size probability curve, and the elements of the grain size probability curve include component types, the overall fine cut-off point of two component types, the most developed component type, and the inclination of the straight line segment. Among them, the component types include rolling component, suspension component, and jumping component, and at least two component types are included in the core.

[0059] The characteristics of sand body thickness and sand-to-shale ratio are obtained based on the statistical analysis of sand body thickness and sand-to-shale ratio data in well logging data interpretation. Combining with the characteristics of well logging curves, the planar distribution pattern of the sand body and the sedimentary evolution characteristics of the profile are inferred. Combining the planar distribution pattern of the sand body and the sedimentary evolution characteristics of the profile with the analysis of paleogeomorphic characteristics can also preliminarily determine the sediment source direction.

[0060] S2. Obtain the oil and gas reservoir reserves and sedimentary microfacies parameters of each research point. The sedimentary microfacies parameters are numerical values, which are any one of channel width, sand body thickness, sand-to-shale ratio, porosity, permeability, and net-to-gross ratio. Among them, there is a good linear relationship between sand body thickness and channel width.

[0061] S3. For each sedimentary microfacies, based on the data of all research points, taking the oil and gas reservoir reserves as the dependent variable y and the sedimentary microfacies parameter as the independent variable x, respectively fit the function model of each sedimentary microfacies. In this embodiment, the square of the correlation R of the function model between the sedimentary microfacies parameter and the oil and gas reservoir reserves under each sedimentary microfacies 2 is greater than 0.95. By comparing the number of oil and gas bearing layers, porosity and permeability, channel sand body thickness and width, effective thickness and net-to-gross ratio, etc. of different sedimentary microfacies, summarizing the characteristics such as oil and gas bearing property, reservoir physical property, sand body width, width-to-thickness ratio, etc. of different sedimentary microfacies and their relationship with the single well productivity, the oil and gas bearing property of each sedimentary microfacies can be determined.

[0062] When the sedimentary microfacies parameter is selected as the sand-to-shale ratio or the sand body thickness, the function model between the sedimentary microfacies parameter and the oil and gas reservoir reserves under each sedimentary microfacies is as follows:

[0063] y = ax 2 + bx + c

[0064] where y is the oil and gas reservoir reserves. x is the sand-to-shale ratio or the sand body thickness. a, b, and c are all constants, obtained by fitting based on the research point data, and different sedimentary microfacies have their corresponding a, b, and c.

[0065] S4. Match the logging data and core data of the area to be studied with the logging curve characteristics, core grain size and heavy mineral characteristics, sand body thickness and sand-to-ground ratio characteristics of each sedimentary microfacies to determine the sedimentary microfacies of the area to be studied; obtain the area Z and sedimentary microfacies parameter X of the area to be studied.

[0066] S5. Based on the sedimentary microfacies of the area to be studied, substitute the sedimentary microfacies parameter X into the function model of the corresponding sedimentary microfacies to calculate the unit oil and gas reservoir reserves Y' of the area to be studied. Calculate the oil and gas reservoir reserves Y of the area to be studied through the following formula:

[0067] The above method for determining the relationship between sedimentary microfacies and oil and gas reservoir reserves is applicable to the cases of complex diversity and large productivity differences in the oil and gas reservoir reserves of braided river deltas and the oil and gas-bearing conditions of sedimentary microfacies in the delta front. This method determines the sedimentary facies type by qualitatively and quantitatively judging the sedimentary environment, fine sand bodies and sand-to-ground ratio, and uses statistical methods to demonstrate the relationship between sedimentary microfacies and oil and gas reservoir reserves, clarifies the favorable sedimentary microfacies and the potential direction of remaining oil and gas evaluation, and provides a reference basis for the engineering design of oil and gas reservoir reserves such as well patterns, well spacing, and well types for oil and gas reservoir productivity construction.

[0068] This embodiment also provides a device for determining the relationship between sedimentary microfacies and oil and gas reservoir reserves, which includes a storage medium and a processor, and a computer program is stored on the storage medium. The processor is used to implement the above method for determining the relationship between sedimentary microfacies and oil and gas reservoir reserves when executing the computer program.

[0069] In summary, this embodiment qualitatively and quantitatively judges the sedimentary environment characteristics through logging data and indoor core test data, combines the sand body thickness and sand-to-ground ratio to delineate, determines the sedimentary microfacies type, and then uses statistical methods to demonstrate the relationship between different sedimentary microfacies and oil and gas-bearing properties, clarifies the favorable sedimentary microfacies and the potential direction of remaining oil and gas evaluation, and provides a reference basis for the engineering design of oil and gas reservoir reserves such as well patterns, well spacing, and well types for oil and gas reservoir productivity construction. Among the prediction methods for oil and gas reservoir reserves in clastic rock reservoirs with the same type of sedimentary environment, this method has a broad application and promotion prospect.

[0070] Embodiment 2

[0071] This embodiment provides a method for determining the relationship between sedimentary microfacies and oil and gas reservoir reserves, which includes the following steps:

[0072] S1. Given a unit area z, different sedimentary microfacies are selected. In this embodiment, the sedimentary microfacies include underwater distributary channel microfacies, channel margin microfacies, mouth bar microfacies, distal bar microfacies, sheet sand microfacies, inter-distributary channel microfacies, and shore-shallow lake mud microfacies. Multiple research points are outlined under each sedimentary microfacies, and the area of each research point is equal to the unit area. For each sedimentary microfacies, well logging data and core data of all its research points are obtained, and the well logging curve characteristics, core grain size and heavy mineral characteristics, sand body thickness and sand-to-shale ratio characteristics of each sedimentary microfacies are statistically analyzed.

[0073] The well logging data includes spontaneous potential well logging curves. In this embodiment, natural gamma well logging curves are added on the basis of spontaneous potential well logging curves. Taking the spontaneous potential well logging curves as the main ones and the natural gamma well logging curves as the auxiliary ones can further improve the analysis accuracy. The well logging curve characteristics include curve amplitude, curve shape, contact relationship, smoothness, tooth midline, thickness, and rhythmicity, as Figure 2 shown.

[0074] The core grain size and heavy mineral characteristics are obtained based on the observation and analysis of a large number of cores on site, and they include characteristics such as average grain size, heavy mineral characteristics, C-M diagrams, etc. for judging sedimentary environments. The core grain size and heavy mineral characteristics also include characteristics such as lithology, color, bedding structure, sorting, roundness, and oil and gas bearing properties for judging paleo-sedimentary environments and hydrodynamic conditions. The heavy mineral characteristics include the average value of the ZTR index and the heavy mineral stability coefficient. The characteristics of the C-M diagram include the shape and trend of the suspension load curve, as Figure 3 shown. The sorting is reflected by the grain size probability curve, as Figure 4 shown. The elements of the grain size probability curve include component types, the overall fine cut-off point of two component types, the most developed component type, and the inclination of the straight line segment. Among them, the component types include rolling components, suspension components, and jump components, and at least two component types are included in the core. In this embodiment, the heavy mineral characteristics also include the ZTR index range, the percentage of stable heavy minerals, and the heavy mineral stability coefficient range. The characteristics of the C-M diagram also include the C mean value and the M mean value. In the C-M diagram, C is the abscissa, representing the grain size index of the particles; M is the ordinate, representing the shape index of the particles. By observing the shape and trend of the curve, different types of suspension load conditions can be judged, such as graded suspension, uniform suspension, etc.

[0075] The sand body thickness and sand-to-shale ratio characteristics are obtained through statistical analysis of the sand body thickness and sand-to-shale ratio data in well logging data interpretation. In this embodiment, the sand body thickness and sand-to-shale ratio are respectively compiled into small layer plane contour maps of sand body thickness and small layer plane contour maps of sand-to-shale ratio for analysis, as Figure 5 、 6As shown in the figure, by combining the characteristics of logging curves, the planar distribution pattern of sand bodies and the sedimentary evolution characteristics of the profile are inferred. In the area where the sand body and the sand-to-ground ratio show a good channel shape, the part with a sand-to-ground ratio greater than 20%, positive rhythm, and medium-thick layers is the underwater distributary channel; the strip-shaped or sheet-like thin sand outside the channel is the channel margin, with weak rhythm and medium-thin layers; the lenticular shape at the end or margin of the channel with reverse rhythm characteristics is the mouth bar, with a small amount of development, medium-thick layers, and poor physical properties; the irregular sheet-like thin sand on the channel margin is the sheet sand; the lenticular and sporadically distributed thin sand outside the channel is the distal bar. Based on the sand body thickness and sand-to-ground ratio, the planar distribution pattern of sand bodies and the sedimentary evolution characteristics of the profile can also be comprehensively judged by combining characteristics such as channel width, effective thickness, effective porosity, and effective permeability, as Figure 7 shown. By combining the planar distribution pattern of sand bodies and the sedimentary evolution characteristics of the profile with the analysis of paleogeomorphic characteristics, the sediment source direction can also be preliminarily determined.

[0076] Taking a certain area as an example, the amplitude of the spontaneous potential curve in this area is generally between 0.42 and 0.89, and the amplitude of the natural gamma curve is generally between 0.32 and 0.76, mainly with low amplitude, indicating insufficient sediment source supply. The curve shapes are mainly bell-shaped and box-shaped, with tooth-shaped widely developed, obvious scouring and filling effects, well-developed scouring surface structures, obvious channel characteristics, and some channels showing lateral migration or gradual abandonment. The contact relationship is mainly uniform or decelerated gradual change, reflecting the characteristics of lateral migration of the channel and subsequent lag of water flow, showing the characteristics of underwater distributary channels. The smoothness is mainly tooth-shaped - micro-tooth-shaped, reflecting the sedimentary characteristics of channel sand with weak hydrodynamic conditions, incomplete transformation, and accompanied by intermittent sedimentary superimposition. The lower part of the tooth midline is mainly characterized by downward inclination, showing the sedimentary characteristics of positive rhythm channels.

[0077] This area is composed of reddish-brown fine sandstone and siltstone, with fine parallel bedding and wavy bedding. The main particle size is 0.06 - 0.12 mm, the maximum particle size is 0.37 mm, and the average grain size is 3.36, with relatively fine lithology. Using the grain size analysis data, the curve mainly shows a "two-stage" or "three-stage" pattern, mainly with a jump component, the fine cut-off point is generally at 3 - 4, the inclination of the straight line segment is 70 - 80°, and the suspension population is relatively developed. Establishing a C-M diagram shows typical traction current channel sedimentary characteristics, with an average C value of 0.2091 and an average M value of 0.1070, mainly with graded suspension and weak hydrodynamic conditions. The sand body has poor sorting, a relatively high mud content, and relatively poor reservoir physical properties. Analyzing the ZTR index of heavy minerals is 0.25 - 0.60, with an average of 0.40; the total amount of stable minerals is 74%, the stability coefficient is 3.39 - 9.67, with an average of 6.57, and the sediment source direction of the heavy mineral index is mainly from the south, with a small amount from the northeast.

[0078] As Figure 8 shown, it is the distribution of sedimentary microfacies in a certain area divided by the above-mentioned logging curve characteristics, core grain size and heavy mineral characteristics, sand body thickness and sand-to-ground ratio characteristics.

[0079] S2. Obtain the oil and gas reservoir reserves and sedimentary microfacies parameters of each research point. The sedimentary microfacies parameters are numerical values, which can be any one of channel width, sand body thickness, sand-to-shale ratio, porosity, permeability, and net-to-gross ratio. Among them, the sand body thickness shows a good linear relationship with the channel width. Taking the center line of the river as the center, a rectangular area representing the channel width extends to both sides. As Figure 9 shown, the relationship between the rectangular area and the sand body thickness is statistically analyzed as P = 0.2384Q - 0.5209. P is the rectangular area, with the unit of km 2 ; Q is the sand body thickness, with the unit of m, and the squared correlation between P and Q is 0.7022.

[0080] S3. For each sedimentary microfacies, based on the data of all its research points, with the oil and gas reservoir reserves as the dependent variable y and the sedimentary microfacies parameters as the independent variable x, fit the function model of each sedimentary microfacies respectively. In this embodiment, the squared correlation R 2 of the function model between the sedimentary microfacies parameters and the oil and gas reservoir reserves under each sedimentary microfacies is greater than 0.95. Compare the number of oil-bearing layers, porosity and permeability, channel sand body thickness and width, effective thickness and net-to-gross ratio, etc. of different sedimentary microfacies, summarize the characteristics of oil-bearing properties, reservoir physical properties, sand body width, width-to-thickness ratio, etc. of different sedimentary microfacies and their relationship with the single-well productivity, and determine that the underwater distributary channel has the best oil-bearing property, with a proportion as high as 65.8%, has good reservoir physical properties, an average porosity of 16.9%, an average permeability of 26 mD, the largest sand body thickness and width, an average sand body thickness of 11.1 m, an average sand body width of 2.1 km2, a low net-to-gross ratio, and an average of 0.459; followed by the channel margin, with a proportion of 25.3%, and the reservoir physical properties are second. The average porosity is 15.1%, the average permeability is 17.4 mD, the sand body thickness and width are smaller, the average sand body thickness is 4.1 m, and the average sand body width is 0.5 km2; the mouth bar and distal bar contain a small amount of oil and gas, and the sheet sand and between the underwater distributary channels do not contain oil and gas.

[0081] When the sedimentary microfacies parameter is selected as the sand-to-shale ratio or the sand body thickness, the function model between the sedimentary microfacies parameter and the oil and gas reservoir reserves under each sedimentary microfacies is as follows:

[0082] y = ax 2 + bx + c

[0083] where y is the oil and gas reservoir reserves. x is the sand-to-shale ratio or the sand body thickness. a, b, and c are all constants, obtained by fitting based on the research point data, and each sedimentary microfacies has its corresponding a, b, and c. In this embodiment, the unit of y is 10 8 m 3 ; x is the sand body thickness, with the unit of m. The function models for specific microfacies are as follows:

[0084] As Figure 10 shown, when the sedimentary microfacies is the underwater distributary channel microfacies, the function model of the sand body thickness and the oil and gas reservoir reserves is:

[0085] y = 0.0368x 2 - 0.187x + 0.2353

[0086] As Figure 11 shown, when the sedimentary microfacies is the channel margin microfacies, the function model of the sand body thickness and the oil and gas reservoir reserves is:

[0087] y = 0.0534x 2 - 0.2878x + 0.4349

[0088] As Figure 12 shown, when the sedimentary microfacies is the sheet sand microfacies or the distal bar microfacies or the mouth bar microfacies, the function model of the sand body thickness and the oil and gas reservoir reserves is:

[0089] y = 0.0095x 2 - 0.0066x - 0.0035

[0090] S4. Match the logging data and core data of the area to be studied with the logging curve characteristics, core grain size and heavy mineral characteristics, sand body thickness and sand-to-shale ratio characteristics of each sedimentary microfacies to determine the sedimentary microfacies of the area to be studied; obtain the area Z and sedimentary microfacies parameter X of the area to be studied.

[0091] S5. Based on the sedimentary microfacies of the area to be studied, substitute the sedimentary microfacies parameter X into the function model of the corresponding sedimentary microfacies to calculate the unit oil and gas reservoir reserve Y' of the area to be studied. Calculate the oil and gas reservoir reserve Y of the area to be studied through the following formula:

[0092] S6. Calculate the single-well controlled reserve by using the material balance method, and determine the economic limit well spacing by using the economic model, so as to provide a potential direction for the evaluation of the oil and gas reservoir reserve and provide a reasonable engineering design reference for the deployment of the production well location, and the calculation formula is as follows:

[0093]

[0094]

[0095] Among them, S is the total cost of single-well drilling and oil construction, in ten thousand yuan / well. p is the average annual gas production operation cost per well, in ten thousand yuan / well / year. A is the economic evaluation price of oil and gas, in yuan / m 3. S, p, and A are obtained through query. E is the recovery factor of the oil and gas reservoir, %, which is the recovery factor of a single well in the same sedimentary microfacies. t is the stable production period of the area to be studied, in years, and t is the quotient of Y divided by the annual production of a single well in the same sedimentary microfacies. d is the economic limit well spacing, in m. G sg is the controlled reserve of a single well, 10 8 m 3 . B is the proven gas-bearing area of the area to be studied, in km 2 , obtained based on the analysis of rock samples and logging curves in the area to be studied. Y is the oil and gas reservoir reserve of the area to be studied, 10 8 m 3 .

[0096] This embodiment also provides a device for determining the relationship between sedimentary microfacies and oil and gas reservoir reserves, which includes a storage medium and a processor. A computer program is stored on the storage medium. The processor is configured to implement the above method for determining the relationship between sedimentary microfacies and oil and gas reservoir reserves when executing the computer program.

[0097] The above are only the preferred embodiments of the present invention and are not used to limit the present invention. For those skilled in the art, various changes and modifications can be made to the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for determining the relationship between sedimentary microfacies and hydrocarbon reservoir reserves, characterized in that: It includes the following steps: S1. Given a unit area z, different sedimentary microfacies are selected, and multiple research points are outlined under each sedimentary microfacies. The area of each research point is equal to the unit area; For each sedimentary microfacies, well logging data and core data of all its research points are obtained. The well logging data includes spontaneous potential logging curves, and the logging curve characteristics, core grain size and heavy mineral characteristics, sand body thickness and sand-to-shale ratio characteristics of each sedimentary microfacies are statistically analyzed; S2. The hydrocarbon reservoir reserves and sedimentary microfacies parameters of each research point are obtained. The sedimentary microfacies parameter is a numerical value, which is any one of channel width, sand body thickness, sand-to-shale ratio, porosity, permeability and net-to-gross ratio; S3. For each sedimentary microfacies, based on the data of all its research points, with the hydrocarbon reservoir reserves as the dependent variable y and the sedimentary microfacies parameter as the independent variable x, a function model of each sedimentary microfacies is respectively fitted; S4. The well logging data and core data of the area to be studied are matched with the logging curve characteristics, core grain size and heavy mineral characteristics, sand body thickness and sand-to-shale ratio characteristics of each sedimentary microfacies to determine the sedimentary microfacies of the area to be studied; The area Z and sedimentary microfacies parameter X of the area to be studied are obtained; S5. Based on the sedimentary microfacies of the area to be studied, substitute the sedimentary microfacies parameter X into the function model of the corresponding sedimentary microfacies to calculate the unit oil and gas reservoir reserves Y' of the area to be studied; calculate the oil and gas reservoir reserves Y of the area to be studied through the following formula:

2. The method for determining the relationship between sedimentary microfacies and oil and gas reservoir reserves according to claim 1, wherein: It also includes S6. The single-well controlled reserves are calculated by the material balance method, and the economic limit well spacing is determined by the economic model. The calculation formula is as follows: Among them, S is the total cost of single-well drilling and oil construction, in ten thousand yuan per well; p is the average annual gas production operation cost per well, in ten thousand yuan per well per year; A is the economic evaluation price of oil and gas, in yuan / m 3 ; S, p, and A are obtained through query; E is the recovery factor of the oil and gas reservoir, %, which is the recovery factor of a single well in the same sedimentary microfacies; t is the stable production period of the area to be studied, in years, and t is the quotient of Y divided by the annual production of a single well in the same sedimentary microfacies; d is the economic limit well spacing, in m; G sg is the controlled reserve of a single well, 10 8 m 3 ; B is the proven gas-bearing area of the area to be studied, in km 2 , which is obtained based on the analysis of rock samples and logging curves in the area to be studied; Y is the oil and gas reservoir reserve of the area to be studied, 10 8 m 3 。 3. The method for determining the relationship between sedimentary microfacies and oil and gas reservoir reserves according to claim 1, characterized in that: The sedimentary microfacies parameter is the sand-to-shale ratio or sand body thickness. The function model between the sedimentary microfacies parameter and the hydrocarbon reservoir reserves under each sedimentary microfacies is as follows: y = ax 2 + bx + c Where y is the hydrocarbon reservoir reserves; x is the sand-to-shale ratio or sand body thickness; a, b, and c are all constants, obtained by fitting based on the research point data, and each sedimentary microfacies has its corresponding a, b, and c.

4. The method for determining the relationship between sedimentary microfacies and oil and gas reservoir reserves according to claim 3, characterized in that: The sedimentary microfacies include subaqueous distributary channel microfacies, channel margin microfacies, mouth bar microfacies, distal bar microfacies, sheet sand microfacies, subaqueous distributary channel interdistributary microfacies, shore-shallow lake mud microfacies.

5. The method for determining the relationship between sedimentary microfacies and hydrocarbon reservoir reserves according to claim 4, wherein: When the sedimentary microfacies parameter is the sand body thickness and the sedimentary microfacies is the subaqueous distributary channel microfacies, the function model between the sand body thickness and the hydrocarbon reservoir reserves is: y = 0.0368x 2 -0.187x + 0.2353 Among them, the unit of y is 10 8 m 3 , and the unit of x is m.

6. The method for determining the relationship between sedimentary microfacies and hydrocarbon reservoir reserves according to claim 4, characterized in that: When the sedimentary microfacies parameter is the sand body thickness and the sedimentary microfacies is the channel margin microfacies, the function model between the sand body thickness and the hydrocarbon reservoir reserves is: y = 0.0534x 2 -0.2878x + 0.4349 where the unit of y is 10 8 m 3 , and the unit of x is m.

7. The method for determining the relationship between sedimentary microfacies and oil and gas reservoir reserves according to claim 4, characterized in that: When the sedimentary microfacies parameter is the sand body thickness and the sedimentary microfacies is the sheet sand microfacies or distal bar microfacies or mouth bar microfacies, the function model between the sand body thickness and the hydrocarbon reservoir reserves is: y = 0.0095x 2 -0.0066x - 0.0035 Among them, the unit of y is 10 8 m 3 , and the unit of x is m.

8. The method for determining the relationship between sedimentary microfacies and hydrocarbon reservoir reserves according to claim 1, characterized in that: The squared correlation R of the function model between the sedimentary microfacies parameters and the oil and gas reservoir reserves under each sedimentary microfacies 2 is greater than 0.

95.

9. The method for determining the relationship between sedimentary microfacies and oil and gas reservoir reserves according to claim 1, wherein: The logging curve characteristics include curve amplitude, curve shape, contact relationship, smoothness, tooth midline, thickness and rhythm.

10. The method for determining the relationship between sedimentary microfacies and oil and gas reservoir reserves according to claim 9, wherein: The well logging data also includes natural gamma logging curves, with the spontaneous potential logging curves as the main and the natural gamma logging curves as the auxiliary.

11. The method for determining the relationship between sedimentary microfacies and hydrocarbon reservoir reserves according to claim 1, characterized in that: The core grain size and heavy mineral characteristics include average grain size, heavy mineral characteristics, C-M diagram.

12. The method for determining the relationship between sedimentary microfacies and hydrocarbon reservoir reserves according to claim 11, characterized in that: The heavy mineral characteristics include the average value of the ZTR index and the heavy mineral stability coefficient.

13. The method for determining the relationship between sedimentary microfacies and hydrocarbon reservoir reserves according to claim 11, wherein: The characteristics of the C-M diagram include the shape and trend of the suspension load curve.

14. The method for determining the relationship between sedimentary microfacies and hydrocarbon reservoir reserves according to claim 11, characterized in that: The core grain size and heavy mineral characteristics also include lithology, color, bedding structure, sorting, roundness and oil and gas bearing property.

15. The method for determining the relationship between sedimentary microfacies and hydrocarbon reservoir reserves according to claim 14, characterized in that: The sorting property is reflected by the grain size probability curve. The elements of the grain size probability curve include the component type, the overall fine cut-off point of two component types, the most developed component type, and the inclination of the straight line segment. Among them, the component types include the rolling component, the suspension component, and the saltation component, and at least two component types are included in the core.

16. Apparatus for determining the relationship between sedimentary microfacies and hydrocarbon reservoir reserves, characterized in that: It includes a storage medium and a processor, and a computer program is stored on the storage medium. The processor is used to implement the method for determining the relationship between sedimentary microfacies and oil and gas reservoir reserves as described in any one of claims 1-15 when executing the computer program.

Images