Method and device for predicting lower limit of permeability depth of sandstone reservoir, equipment and medium

Abstract

The invention relates to a sandstone reservoir permeability depth lower limit prediction method and device, equipment and a medium, and relates to the field of oil and gas exploration and development, and the method comprises the following steps: determining a main reservoir forming period of oil and gas reservoir forming in a research area; recovering the structure uplift denudation amount of the main reservoir forming period in the research area; obtaining the permeability depth lower limit of the sandstone reservoir according to the structural uplift denudation amount-critical burial depth relational expression; wherein the structural uplift denudation amount-critical burial depth relational expression is as follows: y = K * e lambda x, in the expression, y is the critical burial depth, x is the structural uplift denudation amount, K is the lithologic parameter, and lambda is the attenuation coefficient. According to the prediction method provided by the invention, through a specific prediction process, the problems of multi-screen strong denudation cumulative effect and permeability critical burial depth quantification of a research area are solved, and efficient and accurate prediction of the sandstone reservoir permeability depth lower limit is realized.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration and development, specifically to a method, apparatus, equipment, and medium for predicting the lower limit of permeability depth in sandstone reservoirs, and particularly to a method, apparatus, equipment, and medium for predicting the critical depth of the lower limit of permeability in sandstone reservoirs. Background Technology

[0002] The cut-off value of reservoir properties refers to the minimum physical properties required for industrial oil and gas flow in an oil and gas reservoir. It is typically expressed as threshold values ​​for key parameters such as porosity, permeability, and oil saturation. In the field of oil and gas exploration and development, accurately determining the cut-off value of reservoir properties has three core implications: From an economic perspective, the cut-off value directly determines the recoverability and economic viability of the reservoir; for example, reservoirs in the East China Sea with permeability below 1 mD or porosity below 8% are generally difficult to exploit economically. From a geological evaluation perspective, the cut-off value is the scientific boundary between effective reservoirs and non-reservoirs, directly affecting the accuracy of reserve calculations. From the perspective of exploration and development practice, the prediction of the cut-off value provides crucial information for selecting drilling targets, formulating development plans, and designing production enhancement measures.

[0003] Currently, reservoir property lower limit prediction technology has evolved from empirical analogy to quantitative prediction. Traditional methods mainly rely on core experiments and well logging interpretation, determining the lower limit value through static methods such as porosity-permeability cross-sections and oil-bearing occurrence methods. These methods are simple to operate but have obvious limitations: core analysis is costly and the sample representativeness is insufficient; well logging interpretation is significantly affected by the wellbore environment; and empirical formulas are difficult to extrapolate to new areas.

[0004] With the development of geophysical technology and artificial intelligence, the prediction of lower limits of reservoir properties has entered a dynamic, three-dimensional, and intelligent stage. Seismic inversion and attribute analysis enable spatial prediction of reservoir parameters, but the prediction results are subject to limitations in resolution and the tightness of deep to ultra-deep reservoirs, resulting in multiple solutions. Machine learning algorithms establish nonlinear prediction models, which require big data support, have high algorithmic complexity, and are still in the "auxiliary tool" stage. In complex scenarios such as highly heterogeneous regions and multi-phase tectonic zones, the algorithm results still need to be calibrated and reinterpreted.

[0005] In summary, the traditional static model core experiment method, seismic inversion and attribute analysis do not establish a dynamic coupling mechanism, which leads to the prediction results failing to truly reflect the actual geological conditions. At the same time, the dynamic response at the critical depth of permeability is ignored during the prediction process, resulting in poor prediction accuracy. Summary of the Invention

[0006] In view of the problems existing in the prior art, the purpose of the present invention is to provide a method, device, equipment and medium for predicting the lower limit of permeability depth in sandstone reservoirs, so as to solve the defects of traditional static model core test method, seismic inversion and attribute analysis without establishing a dynamic coupling mechanism, which leads to the prediction results not being able to truly reflect the actual geological situation, and the dynamic response of the critical permeability depth being ignored in the prediction process, resulting in poor prediction accuracy.

[0007] To achieve this objective, the present invention adopts the following technical solution:

[0008] In a first aspect, the present invention provides a method for predicting the lower limit of permeability depth in sandstone reservoirs, the prediction method comprising:

[0009] Determine the main hydrocarbon accumulation period in the study area;

[0010] The amount of tectonic uplift and erosion during the main hydrocarbon accumulation period in the study area was restored;

[0011] The lower limit of sandstone reservoir permeability depth is obtained based on the relationship between tectonic uplift erosion and critical burial depth; wherein, the relationship between tectonic uplift erosion and critical burial depth is as follows:

[0012] y = K × e λx

[0013] In the formula, y is the critical burial depth, x is the amount of tectonic uplift and erosion, K is the lithological parameter, and λ is the attenuation coefficient.

[0014] The prediction method provided by this invention solves the problem of quantifying the cumulative effect of multi-stage strong erosion and the critical burial depth of permeability in the study area through a specific prediction process, and realizes efficient and accurate prediction of the lower limit of permeability depth in sandstone reservoirs.

[0015] As a preferred technical solution of the present invention, determining the main hydrocarbon accumulation period in the study area includes: cross-validating the hydrocarbon generation and expulsion history of the source rocks, the trap formation period, and the hydrocarbon charging age of the study area to obtain the main hydrocarbon accumulation period.

[0016] As a preferred technical solution of the present invention, the acquisition of the hydrocarbon generation and expulsion history of the source rock includes: performing basin inversion thermal evolution history to simulate the vitrinite reflectance Ro.

[0017] As a preferred technical solution of the present invention, the method for obtaining the trap formation period includes one or a combination of at least two of the following: growth fault analysis, stratigraphic stripping technology, or fission track thermal history inversion.

[0018] As a preferred technical solution of the present invention, the oil and gas charging age is obtained by means of the homogenization temperature of reservoir oil and gas inclusions.

[0019] As a preferred technical solution of the present invention, the cross-validation analysis includes: data validation analysis, temporal coupling quantification, and hydrocarbon accumulation intensity analysis.

[0020] Preferably, the data verification analysis includes: time window overlap verification or non-overlapping contradictory data parsing.

[0021] Preferably, the determination of the cross-validation analysis includes: meeting the Level I standard, Level II standard, or Level III standard.

[0022] Preferably, the Level I criteria include: simultaneously satisfying the following two conditions: overlapping time windows of the three elements and high-intensity accumulation with an inclusion abundance of >15 per thin section and a gas and oil saturation of >60%.

[0023] Preferably, the Level II criteria include: satisfying (1) only two elements overlap + high-intensity evidence of hydrocarbon accumulation or (2) three elements overlap but the intensity of hydrocarbon accumulation is moderate with an oil saturation of 40-50%.

[0024] Preferably, the Level III criteria include: meeting the requirements of no time window overlap and low-intensity accumulation with an inclusion abundance of <5 inclusions / section.

[0025] As a preferred technical solution of the present invention, the method for restoring the amount of tectonic uplift and erosion during the main hydrocarbon accumulation period in the study area includes one or a combination of at least two of the following: stratigraphic trend extrapolation method, vitrinite reflectance Ro method, apatite fission track AFT method, or acoustic transit time Δlogt method.

[0026] Secondly, the present invention provides a device for predicting the lower limit of permeability depth in sandstone reservoirs, the device comprising:

[0027] The module for obtaining the main hydrocarbon accumulation period determines the main hydrocarbon accumulation period in the study area.

[0028] The module for obtaining tectonic uplift and erosion data reconstructs the tectonic uplift and erosion data during the main hydrocarbon accumulation period in the study area.

[0029] The prediction module obtains the lower limit of sandstone reservoir permeability depth based on the relationship between tectonic uplift erosion and critical burial depth.

[0030] The relationship between the tectonic uplift erosion amount and the critical burial depth is as follows:

[0031] y = K × e λx

[0032] In the formula, y is the critical burial depth, x is the amount of tectonic uplift and erosion, K is the lithological parameter, and λ is the attenuation coefficient.

[0033] Thirdly, the present invention provides an electronic device, the electronic device comprising:

[0034] At least one processor; and a memory communicatively connected to said at least one processor;

[0035] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the method for predicting the lower limit of permeability depth in sandstone reservoirs as described in the first aspect.

[0036] Fourthly, embodiments of the present invention provide a computer storage medium storing computer-executable instructions, which, when executed by a processor, implement the method for predicting the lower limit of permeability depth in sandstone reservoirs as described in the first aspect.

[0037] Compared with existing technical solutions, the present invention has the following beneficial effects:

[0038] (1) The prediction method provided by this invention reveals the law of exponential decay of critical burial depth of permeability as erosion increases, solves the problem of quantifying the cumulative effect of multi-stage strong erosion and critical burial depth of permeability in the study area, and overcomes the geological problems in the prediction of traditional static models.

[0039] (2) The prediction method provided by this invention constructs a critical burial geological model with a lower limit of permeability (1mD) based on the amount of erosion, generates a spatial distribution critical burial depth prediction map, drives exploration and development to reduce costs and increase efficiency, and provides key basis for drilling target area selection, development plan formulation and production enhancement measures design. Attached Figure Description

[0040] Figure 1 This is a flowchart of a method for predicting the lower limit of permeability depth in sandstone reservoirs provided by an embodiment of the present invention;

[0041] Figure 2 This is a schematic diagram of a device for predicting the lower limit of permeability depth in sandstone reservoirs provided in an embodiment of the present invention;

[0042] Figure 3 This is a schematic diagram of an electronic device provided in an embodiment of the present invention;

[0043] Figure 4 This is a planar distribution diagram of the ridge erosion amount in the study area in Embodiment 1 of the present invention;

[0044] Figure 5 This is a prediction chart of the critical burial depth of permeability in fine sandstone reservoirs according to Embodiment 1 of the present invention;

[0045] Figure 6 This is a prediction chart of the critical burial depth of permeability in sandstone reservoirs according to Embodiment 1 of the present invention;

[0046] In the diagram: 100 - Main hydrocarbon accumulation period acquisition module, 200 - Tectonic uplift and erosion amount acquisition module, 300 - Prediction module;

[0047] 10-Electronic device, 11-Processor, 12-ROM, 13-RAM, 14-Bus, 15-I / O interface, 16-Input unit, 17-Output unit, 18-Storage unit, 19-Communication unit.

[0048] The present invention will now be described in further detail. However, the examples described below are merely simplified examples of the present invention and do not represent or limit the scope of protection of the present invention. The scope of protection of the present invention is determined by the claims. Detailed Implementation

[0049] To better illustrate the present invention and facilitate understanding of its technical solutions, typical but non-limiting embodiments of the present invention are as follows:

[0050] I. This embodiment provides a method for predicting the lower limit of permeability depth in sandstone reservoirs, the process of which is as follows: Figure 1 As shown, the prediction method includes:

[0051] Determine the main hydrocarbon accumulation period in the study area;

[0052] The amount of tectonic uplift and erosion during the main hydrocarbon accumulation period in the study area was restored;

[0053] The lower limit of sandstone reservoir permeability depth is obtained based on the relationship between tectonic uplift erosion and critical burial depth; wherein, the relationship between tectonic uplift erosion and critical burial depth is as follows:

[0054] y = K × e λx

[0055] In the formula, y is the critical burial depth, x is the amount of tectonic uplift and erosion, K is the lithological parameter, and λ is the attenuation coefficient.

[0056] In this invention, lithological parameters can be obtained according to conventional technical requirements in the field, such as K = 4870 for fine sandstone and K = 4960.5 for medium sandstone; the attenuation coefficient λ can be obtained according to conventional procedures in the field, for example λ = -2 × 10 -4 m -1 .

[0057] The determination of the main hydrocarbon accumulation period in the study area includes: cross-validation analysis of the hydrocarbon generation and expulsion history of the source rocks, the trap formation period, and the hydrocarbon charging age in the study area to obtain the main hydrocarbon accumulation period.

[0058] The acquisition of the hydrocarbon generation and expulsion history of the source rocks includes: performing basin inversion thermal evolution history to simulate vitrinite reflectance Ro.

[0059] For example, the thermal evolution history is inverted using the basin simulation software (PetroMod) to simulate the vitrinite reflectance (Ro).

[0060] The methods for obtaining the formation period of the trap include one or a combination of at least two of the following: growth fault analysis, stratigraphic stripping technology, or fission track thermal history inversion.

[0061] In this invention, the growth fault analysis method refers to the continuous activity of growth faults (co-depositional faults) during the depositional process, resulting in a significantly greater thickness of the downthrown strata than the upthrown strata (downthrown strata thickness / upthrown strata thickness = growth index GI, GI>1 indicates an active fault period; GI=1 indicates a dormant fault period; GI<1 indicates the fault may be dormant or its properties may be reversed). The displacement difference generated by fault activity forms structural traps such as fault noses and fault blocks; therefore, the formation period of the traps can be determined by analyzing the fault activity period.

[0062] In this invention, the stratigraphic stripping technique refers to the process of gradually stripping away sedimentary layers and correcting for compaction effects to reconstruct the burial history and paleotectonic morphology of traps and determine the formation time of traps.

[0063] In this invention, fission track thermal history inversion refers to the fact that trap formation is often accompanied by tectonic uplift, leading to formation cooling which is recorded by the fission track system. By analyzing the cooling time-temperature nodes in the inverted thermal history curve, the critical period for trap formation can be identified.

[0064] The age of the oil and gas filling is obtained by means of the homogenization temperature of the reservoir oil and gas inclusions.

[0065] In this invention, obtaining the hydrocarbon charging age by means of the homogenization temperature of reservoir hydrocarbon inclusions refers to inverting the hydrocarbon charging age using the homogenization temperature (Th) of reservoir hydrocarbon inclusions. Specifically, this is achieved by coupling the inclusion capture temperature with the burial thermal history curve. The homogenization temperature measured by the inclusion (representing the lowest temperature at which hydrocarbons are charged) is projected onto the thermal history curve of the target reservoir. The principle is that during its burial history, the reservoir can only form inclusions at that temperature when its temperature reaches or exceeds the homogenization temperature of the inclusions. After the inclusions are formed, the captured temperature information is "frozen" and preserved. Specifically, on the thermal history curve, the time period corresponding to the homogenization temperature value of the inclusions is the time when the hydrocarbon charging event represented by that hydrocarbon inclusion occurred.

[0066] The cross-validation analysis includes: data validation analysis, temporal coupling quantification, and hydrocarbon accumulation intensity analysis.

[0067] The data verification analysis includes: time window overlap verification or non-overlapping contradictory data analysis.

[0068] The criteria for cross-validation analysis include: meeting Level I, Level II, or Level III standards.

[0069] Among them, the Level I standard must simultaneously meet the following two conditions: overlapping time windows of the three elements; and high-intensity evidence of hydrocarbon accumulation (abundance of inclusions >15 per section and gas and oil saturation >60%).

[0070] In this invention, the overlap of the three-element time windows refers to the determination formula being: Main accumulation period = {t | t∈T} 排烃 ∩t∈T 圈闭 ∩t∈T 充注 For example, the hydrocarbon expulsion window of the source rock is 16-6 Ma, the trap formation is 14-5.3 Ma, the oil and gas injection is 7.2±0.8 Ma, and the overlapping window is 7.2-6 Ma. That is, take the intersection of the three, and the overlap of two elements can be deduced in the same way.

[0071] Among them, the Class II standard meets any one of the following criteria: (1) Only two elements overlap + high-intensity evidence of hydrocarbon accumulation; (2) Three elements overlap but the intensity of hydrocarbon accumulation is moderate (oil saturation 40-50%).

[0072] Among them, the Level III criteria are: no overlapping time windows (even if the single-element evidence is strong); low-intensity accumulation (abundance of inclusions <5 per thin section).

[0073] The methods for restoring the amount of tectonic uplift and erosion during the main hydrocarbon accumulation period in the study area include: stratigraphic trend extrapolation method, vitrinite reflectance Ro method, apatite fission track AFT method, and acoustic transit time Δlogt method.

[0074] In this invention, other optimized methods in the field can also be used to restore the amount of tectonic uplift and erosion during the main hydrocarbon accumulation period in the study area, such as:

[0075] In the study area, benchmark wells were selected to obtain the uplift and erosion amount ΔH0 and the time-depth conversion relationship of the target layer in the benchmark wells; standard layers were selected, and the depth T of the top interface of the three-dimensional structure of the marker layer was reconstructed based on the time-depth conversion relationship of the benchmark wells. n The uplift and erosion volume X of the target formation is calculated based on the uplift and erosion volume ΔH0 of the benchmark well and the paleotectonic surface of the marker layer. n .

[0076] The benchmark well is located in the key part of the anticline axis and the hanging wall of the fault, and can control the main structural units of the study area.

[0077] The benchmark well contains cuttings / core logging data for the entire well section, systematic logging data, and precise stratification data.

[0078] The benchmark well encountered the target formation of the Late Miocene and was not strongly altered by later faults.

[0079] Among them, the drilling samples from the benchmark well can meet the requirements of apatite fission track AFT and (U-Th) / He thermochronological analysis.

[0080] The process of obtaining the uplift erosion amount ΔH0 includes: selecting samples from the benchmark well below the Late Miocene unconformity surface for apatite and zircon fission track testing and (U-Th) / He age testing, then performing thermal history inversion simulation to obtain simulation results, and calculating the uplift erosion amount ΔH0 based on the simulation results.

[0081] In this invention, the sample from the reference well below the Late Miocene unconformity is obtained by continuous sampling, with the sampling interval being 50-100m.

[0082] In this invention, the uplift erosion amount ΔH0 is calculated by constraining the uplift cooling time through fission tracks.

[0083] The simulation results include: cooling amplitude ΔT and paleogeothermal gradient G.

[0084] In this invention, the simulation results also include: temperature-time (Tt) trajectory, rapid cooling event (7.2±0.8 Ma), vitrinite reflectivity Ro, etc.

[0085] In this invention, the paleothermal gradient G is obtained through fluid inclusion inversion.

[0086] The formula for calculating the uplift erosion amount ΔH0 includes: ΔH0 = Cooling amplitude ΔT / Paleogeothermal gradient G.

[0087] The process of obtaining the time-depth conversion relationship includes: selecting wavelet and reflection coefficient sequences extracted from seismic data for convolution operation to generate a simulated seismic trace; comparing the time domain of the seismic trace with the actual seismic trace near the well to ensure that the main reflection peak / trough on the synthetic record and the key in-phase axis of the seismic trace can be optimally matched in terms of time, phase and amplitude characteristics, thereby obtaining the time-depth conversion relationship of the reference well.

[0088] In this invention, time, phase, and amplitude characteristics are optimally matched. Time matching refers to precise alignment of geological interfaces, specifically: the peak / trough time difference ≤ 1 / 8 of the dominant wavelength (usually < 5 ms); the key layer time difference (e.g., unconformity, reservoir top) ≤ 3 ms; and the error between the synthetic record time domain and the seismic trace time domain velocity model < 3%. Phase matching refers to eliminating waveform distortion, specifically: for polarity consistency, the geological interfaces corresponding to peaks / troughs have the same properties (e.g., peak = sandstone top); the residual between the synthetic record wavelet phase spectrum and the seismic trace phase spectrum < 10°; phase stability, with a phase rotation angle change of < 5° within the time window (20-80 Hz band); and amplitude matching refers to reflecting lithological changes, specifically: relative amplitude maintenance, with a reservoir / non-reservoir amplitude ratio error < 15%; and balanced frequency band energy, with an energy difference of < 10% in the dominant frequency band (20-50 Hz). Impedance trend matching is also achieved, with a correlation coefficient > 0.8 between the synthetic record and the seismic trace envelope morphology.

[0089] In this invention, the time-depth conversion relationship is obtained by calculating the cumulative propagation time using acoustic logging integrals or by using empirical formulas for regional velocity.

[0090] In this invention, the acquisition of time-depth conversion relationship involves checking the consistency of the depth reference surface of the data (such as sonic logging, density logging, seismic data (wellside channel)) (such as logging depth, drilling layer depth, seismic processing reference surface).

[0091] The standard layer is located close to and below the unconformity surface, is uneroded, and can record the original structural morphology of tectonic movements.

[0092] In this invention, the selected marker layer has the characteristics of strong amplitude, high continuity, and consistent polarity.

[0093] In this invention, strong amplitude refers to the seismic reflected wave energy being significantly higher than the background noise and the reflection from adjacent strata, with a relative amplitude ratio ≥ 3 times the average amplitude of the background strata.

[0094] In this invention, high continuity refers to the stable lateral extension of the reflection phase axis, consistent waveform, few fractures or lithological interruptions, a continuity index of 0.85, and fault cutting <5%.

[0095] In this invention, uniform polarity means that the top interface of the marker layer exhibits a uniform phase (peak / trough) throughout the entire work area.

[0096] Wherein, the top interface depth T of the three-dimensional structure of the marker layer n The reconstruction process includes: performing fine-scale mesh interpretation on the top surface of the marker layer and reconstructing the depth T of the three-dimensional structural top interface of the marker layer based on the time-depth conversion relationship of the reference well. n .

[0097] In this invention, the grid spacing in the fine grid structure interpretation can be selected as (20-30m)×(20-30m), which can be selected according to the actual requirements.

[0098] Wherein, the uplift erosion amount X n The calculation process includes: based on the depth T0 of the top surface of the marker layer of the reference well and the depth T of the top interface of the three-dimensional structure of the marker layer. n The relative uplift ΔH was calculated. n Then, based on the relative uplift ΔH n Draw a contour map of the uplift and erosion amount ΔH0, based on the relative uplift amount ΔH n The uplift and erosion amount X of the target stratum is calculated from the uplift and erosion amount ΔH0. n .

[0099] In this invention, the contour map of uplift and erosion amount ΔH0 can intuitively display the relative three-dimensional spatial undulation of the marker layer, and determine the relative uplift / subsidence trend of the strata. In the figure, if ΔH n If ΔH > 0, then the uplift of the top boundary of the marker layer relative to the reference well; if ΔH n <0, then the settlement of the top boundary of the marker layer relative to the reference well; if ΔH n =0, then the reference well point and the top boundary of the marker layer are at the same structural height.

[0100] Wherein, the relative uplift amount ΔH n The calculation formula is as follows:

[0101] ΔH n =T0-T n

[0102] In the formula, T0 is the depth of the top surface of the marker layer of the reference well, in meters; T n Let m be the depth of the top interface of the three-dimensional construction of the marker layer.

[0103] In this invention, the uplift and erosion amount X of the target stratum n In the calculation, a spatial continuous erosion model is generated by combining the seismic sequence lattice with the compaction correction coefficient.

[0104] Wherein, the uplift and erosion amount X of the target stratum n The calculation formula is as follows:

[0105] X n =(ΔH0+ΔH) n )×C

[0106] In the formula, ΔH0 is the uplift erosion amount, in meters; ΔH n , where m is the relative uplift; C is the compaction correction factor.

[0107] In this invention, the compaction correction coefficient can be obtained according to conventional methods in the art. For example, as follows: During sediment burial, the pressure of the overlying strata causes a decrease in porosity and a thinning of the sediment. The decompaction correction is performed using a porosity-depth relationship model to inversely reconstruct the paleothickness at the end of sedimentation: C = (1-φ) / ( ... paleo ) / (1-φ now In the formula, φ now The average current porosity of the formation is obtained through statistical analysis of well logging data or laboratory core analysis; φ paleo φ represents the average paleoporosity at the end of stratigraphic deposition. paleo =φ0*e -Cc*Xn Xn represents the uplift and erosion amount of the target stratum; φ0 (sandstone = 0.42, mudstone = 0.68); Cc (sandstone = 0.35 km²). -1 Mudstone = 0.48 km -1 ).

[0108] II. This embodiment provides a device for predicting the lower limit of permeability depth in sandstone reservoirs, such as... Figure 2 As shown, the prediction device includes:

[0109] Module 100, which obtains the main hydrocarbon accumulation period, determines the main hydrocarbon accumulation period in the study area.

[0110] Module 200 for obtaining tectonic uplift and erosion data, reconstructing the tectonic uplift and erosion data during the main hydrocarbon accumulation period in the study area;

[0111] Prediction module 300 obtains the lower limit of sandstone reservoir permeability depth based on the relationship between tectonic uplift erosion and critical burial depth.

[0112] The relationship between the tectonic uplift erosion amount and the critical burial depth is as follows:

[0113] y = K × e λx

[0114] In the formula, y is the critical burial depth, x is the amount of tectonic uplift and erosion, K is the lithological parameter, and λ is the attenuation coefficient.

[0115] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0116] III. This invention provides an electronic device intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0117] like Figure 3 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded into the RAM 13 from storage unit 18. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An I / O interface 15 is also connected to the bus 14.

[0118] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0119] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the aforementioned method for predicting the lower limit of permeability depth in sandstone reservoirs.

[0120] In some embodiments, the aforementioned method for predicting the lower limit of permeability depth in sandstone reservoirs can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the aforementioned method for predicting the lower limit of permeability depth in sandstone reservoirs described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the aforementioned method for predicting the lower limit of permeability depth in sandstone reservoirs by any other suitable means (e.g., by means of firmware).

[0121] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0122] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0123] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0124] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0125] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0126] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0127] The server provided in this embodiment includes: a memory, a processor, and a computer program stored in the memory and capable of running on the processor. When the processor executes the program, it implements the aforementioned method for predicting the lower limit of permeability depth in sandstone reservoirs.

[0128] Unless otherwise specifically stated, terms such as processing, calculation, operation, determination, display, etc., may refer to the actions and / or processes of one or more processing or computing systems or similar devices that represent the manipulation and conversion of data representing physical (e.g., electronic) quantities within the registers or memory of the processing system into other data similarly representing physical quantities within the memory, registers, or other such information storage, transmission, or display devices of the processing system. Information and signals can be represented using any of a variety of different techniques and methods. For example, data, instructions, commands, information, signals, bits, symbols, and chips mentioned throughout the above description can be represented by voltage, current, electromagnetic waves, magnetic fields or particles, light fields or particles, or any combination thereof.

[0129] Those skilled in the art will also understand that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with embodiments of the present invention can all be implemented as electronic hardware, computer software, or a combination thereof. To clearly illustrate the interchangeability between hardware and software, the various illustrative components, blocks, modules, circuits, and steps described above are generally described in terms of their functionality. Whether this functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. Those skilled in the art can implement the described functionality in alternative ways for each specific application; however, such implementation decisions should not be construed as departing from the scope of protection of the present invention.

[0130] The steps of the methods or algorithms described in conjunction with the embodiments herein can be directly embodied in hardware, software modules executed by a processor, or a combination thereof. The software modules can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disks, removable disks, CD-ROMs, or any other form of storage medium well known in the art. An exemplary storage medium is connected to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and storage medium can reside in an ASIC. The ASIC can reside in a user terminal. Alternatively, the processor and storage medium can exist as discrete components in the user terminal.

[0131] For software implementation, the techniques described in this invention can be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. This software code can be stored in memory units and executed by a processor. The memory units can be implemented within the processor or externally; in the latter case, they are communicatively coupled to the processor via various means, as is well known in the art.

[0132] Furthermore, to illustrate the present invention, practical examples are used for explanation, as follows:

[0133] Example 1

[0134] This embodiment provides a prediction process for the lower limit of permeability depth in sandstone reservoirs, specifically for the Xihu Depression in the East China Sea Basin, as follows:

[0135] 1) First, determine the main hydrocarbon accumulation period in the study area, as follows:

[0136] Determining the main hydrocarbon accumulation period requires a comprehensive analysis of three factors: the hydrocarbon generation and expulsion history of source rocks, the trap formation period, and the hydrocarbon charging age, combined with cross-verification using multiple geological and geochemical methods.

[0137] ① Analysis of the hydrocarbon generation and expulsion history of source rocks:

[0138] Vitrin reflectance (Ro) simulation: Thermal evolution history was retrieved using the basin simulation software (PetroMod).

[0139] T max =10 0.018*Ro+1.52

[0140] Hydrocarbon generation threshold: Ro = 0.6% (starting point of oil generation), Ro = 1.3% (peak of gas generation). Peak hydrocarbon generation of Pinghu Formation source rocks: oil generation 16-12 Ma (Ro = 0.8-1.0%), gas generation 10-6 Ma (Ro = 1.3-2.0%).

[0141] ②The time constraint for trap formation is shown in Table 1 below:

[0142] Table 1

[0143]

[0144] ③ Direct dating of oil and gas charging: Homogenization temperature of reservoir oil and gas inclusions, with main reservoir formation at 5-7 Ma.

[0145] Based on comprehensive analysis, the main hydrocarbon accumulation period in the study area was determined to be 5.5±0.3 Ma (Late Miocene Longjing Movement II).

[0146] 2) Secondly, the tectonic uplift and erosion during the main hydrocarbon accumulation period in the study area were restored.

[0147] A three-dimensional quantitative method for reconstructing the thickness of tectonic uplift and erosion in hydrocarbon basins based on chronological constraints was applied to perform a detailed reconstruction of the paleotectonic morphology of the target area.

[0148] 1) First, select a benchmark well from the main hydrocarbon accumulation period and establish the uplift and erosion volume of the benchmark well.

[0149] Selection criteria for benchmark drilling:

[0150] ①Located in a relatively stable structural region, at a key location on the hanging wall of a fault, it can control the main structural units of the study area.

[0151] ② It has full-section cuttings / core logging, systematic logging (sonic, density, gamma), and precise stratified data.

[0152] ③ The drilling encountered the target strata of the Late Miocene (such as the Miocene Yuquan Formation in the East China Sea Shelf Basin), which had not been strongly altered by later faults.

[0153] ④ The well has sufficient core or rock cutting samples to meet the requirements of apatite fission track AFT and (U-Th) / He thermochronological analysis.

[0154] Key steps in measuring uplift and erosion at the benchmark well point:

[0155] ① Sample collection and mineral sorting: Continuous sampling (at 80m intervals) was conducted below the Late Miocene unconformity surface, with the lithology being sandstone. Rock fragments were screened and washed with water, and apatite and zircon were separated using internationally accepted heavy liquid and magnetic separation techniques.

[0156] ② Fission track testing of apatite and zircon and (U-Th) / He age testing.

[0157] ③ The temperature-time (Tt) trajectory, rapid cooling event (7.2±0.8 Ma), cooling amplitude ΔT (18±1℃), Ro, and paleothermal gradient G (34±2℃ / km) experienced by the benchmark well sample during the main hydrocarbon accumulation period were obtained by thermal history simulation and inversion.

[0158] ④ Calculation principle of erosion amount: ΔH0=ΔT / G, from which the erosion amount of the target formation in the benchmark well is obtained as 559m.

[0159] 2) Secondly, the uplift from the benchmark well to the 3D seismic interpretation interface is calculated. The key steps are as follows:

[0160] ① Time-depth calibration of benchmark wells and seismic data volumes:

[0161] i. Data preparation and quality control: High-quality sonic logging, density logging, and seismic data (wellside path); accurate drilling stratification data (geological marker layer depth); checking the consistency of the depth reference surface of the data (logging depth, drilling stratification depth, seismic processing reference surface).

[0162] ii. Establishing the initial time-depth relationship: The cumulative propagation time is usually calculated using sonic logging integrals or by using empirical formulas for regional velocities.

[0163] iii. Synthesis record creation and calibration:

[0164] A suitable wavelet (extracted from seismic data) is selected and convolved with the reflection coefficient sequence to generate a simulated seismic trace—a synthetic seismic record. The synthetic seismic trace (time domain) is compared with the actual seismic trace near the well (time domain). The time-depth relationship is repeatedly adjusted by stretching, compressing, or shifting the record to achieve optimal matching of the main reflection peaks / troughs on the synthetic record with the key phase axes of the seismic trace in terms of time, phase, and amplitude characteristics. Finally, a precise time-depth pair and time-depth conversion relationship for the reference well location are obtained.

[0165] 3) Select the marker layer and reconstruct the three-dimensional interface.

[0166] ① A marker layer, uneroded and located directly below the unconformity, is selected to ensure the recording of the original tectonic morphology. The top interface of the marker layer exhibits strong amplitude, high continuity, consistent polarity, and continuous tracking throughout the entire area.

[0167] ② A fine structural interpretation of the top surface of the marker layer was performed with a grid spacing of 25m×25m. Based on the time-depth conversion relationship of the reference well, the depth T of the top interface of the three-dimensional structure of the marker layer was reconstructed. n .

[0168] 4) Finally, the uplift and erosion amounts are calculated by comparing the erosion amount of the quasi-well with the paleotectonic surface of the marker layer.

[0169] ①Refer to the benchmark well and calculate the relative uplift ΔH at the top interface of the marker layer. n The formula is as follows:

[0170] ΔH n =T0-T n

[0171] In the formula, T0 is the depth of the top surface of the marker layer of the reference well, in meters; T n The depth of the top interface of the marker layer in 3D construction is m;

[0172] Calculation steps:

[0173] i. Determine the benchmark well data. Obtain the depth value T0 of the top surface of the marker layer in the benchmark well (reference well).

[0174] ii. Extract the 3D structure of the marker layer and construct the top interface depth T n data.

[0175] iii. Substitute into the formula ΔH n =T0-T n It can calculate the relative uplift and draw ΔH0 contour maps to visually display the relative undulations of the marker layer in three-dimensional space and determine the relative uplift / subsidence trend of the strata.

[0176] Geological significance:

[0177] ΔH n >0: The uplift of the top boundary of the marker layer relative to the reference well.

[0178] ΔH n <0: Settlement of the top boundary of the marker layer relative to the reference well.

[0179] ΔH n =0: The reference well point and the top boundary of the marker layer are at the same structural height.

[0180] ②Based on the relative uplift ΔH at the top interface of the marker layer n Calculate the uplift and erosion amount of the target stratum X n The formula is as follows:

[0181] X n =(ΔH0+ΔH) n )×C

[0182] In the formula, ΔH0 is the uplift erosion amount, in meters; ΔH n , where m is the relative uplift; C is the compaction correction factor.

[0183] X n The calculation results of the uplift and erosion amount during the main hydrocarbon accumulation period of the ≥0 target strata are shown in the figure. Figure 4The results showed that the overall tectonic uplift erosion in the study area ranged from 500 to 1750 m. This erosion exhibited significant spatial variability in its planar distribution, displaying a regular zonation: the erosion intensity was highest in the tectonic core region, with erosion amounts generally reaching 1200-1800 m; while towards the tectonic limbs, the erosion intensity significantly decreased, with erosion amounts dropping to 500-1200 m.

[0184] 3) A coupled model of uplift erosion and critical burial depth of sandstone permeability (1mD) is used for prediction, as detailed below:

[0185] ① Core and wellbore core samples were selected from representative deep sandstone reservoirs in the study area. Permeability experiments (such as gas method and pressure pulse method) were conducted under simulated formation conditions to obtain core parameters characterizing reservoir seepage capacity.

[0186] ② The erosion amount and critical burial depth corresponding to the lower limit of low permeability (1mD) of medium sandstone and fine sandstone in deep drilling in the study area were statistically analyzed. Based on the physical property system analysis of core and wellbore core samples from deep drilling in the study area, the geological parameters of erosion amount and critical burial depth corresponding to the lower limit of low permeability (1mD) of medium sandstone and fine sandstone reservoirs were statistically determined. The critical burial depth refers to the burial depth corresponding to a low permeability of 1mD in medium sandstone and fine sandstone reservoirs.

[0187] Based on the systematic integration of erosion recovery data and critical depth information of deep dense medium sandstone and fine sandstone, this embodiment predicts a quantitative dynamic correlation model between tectonic uplift erosion volume x and critical burial depth y, and a permeability critical burial depth prediction chart, as shown in the following formula and... Figure 5 and Figure 6 The mathematical expression of the model is as follows:

[0188] Fine sandstone: y = 4870 × e -0.0002x R 2 =0.9785

[0189] Medium sandstone: y=4960.5×e -0.0002x R 2 =0.9831

[0190] In the formula, y is the lower limit of the depth corresponding to 1 mD of permeability, i.e., the critical burial depth, in m; x is the amount of tectonic uplift erosion, in m;

[0191] Prediction chart of critical burial depth for permeability of sandstone reservoirs ( Figure 5 and Figure 6 It includes the following core features:

[0192] ① Definition of Plate Structure

[0193] A two-dimensional coordinate system is constructed using tectonic uplift erosion (x-axis) and critical burial depth (y-axis); the curve in the figure is the critical burial depth curve, and its mathematical expression is: y = K × e λx (K is the lithological parameter, K = 4870 for fine sandstone, K = 4960.5 for medium sandstone; λ is the attenuation coefficient, λ = -2.0 × 10⁻⁶) -4 m -1 );

[0194] ② The rules for dividing the region are shown in Table 2 below.

[0195] Table 2

[0196]

[0197] ③ Geological connotations of the curve

[0198] The critical burial depth curve characterizes the permeability threshold response: each point on the curve corresponds to the critical burial depth with a permeability of 1 mD.

[0199] Dynamic coupling mechanism: The curve shape reflects the exponential decay relationship between tectonic uplift erosion amount x and critical burial depth y.

[0200] The present invention is described in detail through the above embodiments, but the present invention is not limited to the above detailed structural features, that is, it does not mean that the present invention must rely on the above detailed structural features to be implemented. Those skilled in the art should understand that any improvements to the present invention, equivalent substitutions for the components used in the present invention, additions of auxiliary components, and selection of specific methods, etc., all fall within the protection scope and disclosure scope of the present invention.

[0201] The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present invention, various simple modifications can be made to the technical solution of the present invention, and these simple modifications all fall within the protection scope of the present invention.

[0202] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not describe the various possible combinations separately.

[0203] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the present invention, they should also be regarded as the content disclosed by the present invention.

Claims

1. A method for predicting the lower limit of permeability depth in sandstone reservoirs, characterized in that, The prediction method includes: Determine the main hydrocarbon accumulation period in the study area; The amount of tectonic uplift and erosion during the main hydrocarbon accumulation period in the study area was restored; The lower limit of sandstone reservoir permeability depth is obtained based on the relationship between tectonic uplift erosion and critical burial depth. The relationship between the tectonic uplift erosion amount and the critical burial depth is as follows: y=K×e λx In the formula, y is the critical burial depth, x is the amount of tectonic uplift and erosion, K is the lithological parameter, and λ is the attenuation coefficient.

2. The prediction method as described in claim 1, characterized in that, The determination of the main hydrocarbon accumulation period in the study area includes: cross-validation analysis of the hydrocarbon generation and expulsion history of the source rocks, the trap formation period, and the hydrocarbon charging age in the study area to obtain the main hydrocarbon accumulation period.

3. The prediction method as described in claim 2, characterized in that, The acquisition of the hydrocarbon generation and expulsion history of the source rocks includes: performing basin inversion thermal evolution history to simulate vitrinite reflectance Ro.

4. The prediction method as described in claim 2, characterized in that, The methods for obtaining the trap formation period include one or a combination of at least two of the following: growth fault analysis, stratigraphic stripping technology, or fission track thermal history inversion.

5. The prediction method as described in claim 2, characterized in that, The age of the oil and gas filling was obtained by means of the homogenization temperature of the reservoir oil and gas inclusions.

6. The prediction method according to any one of claims 1-5, characterized in that, The cross-validation analysis includes: data validation analysis, temporal coupling quantification, and hydrocarbon accumulation intensity analysis; Preferably, the data verification analysis includes: time window overlap verification or non-overlapping contradictory data parsing; Preferably, the determination of the cross-validation analysis includes: meeting the Level I standard, Level II standard, or Level III standard; Preferably, the Level I standard includes: simultaneously meeting the following two conditions: the three-element time windows overlap and the high-intensity accumulation is characterized by an inclusion abundance of >15 per thin section and a gas and oil saturation of >60%; Preferably, the Level II criteria include: satisfying (1) only two elements overlap + high-intensity evidence of hydrocarbon accumulation or (2) three elements overlap but the intensity of hydrocarbon accumulation is moderate with an oil saturation of 40-50%; Preferably, the Level III criteria include: meeting the requirements of no time window overlap and low-intensity accumulation with an inclusion abundance of <5 inclusions / section.

7. The prediction method according to any one of claims 1-6, characterized in that, The methods for restoring the amount of tectonic uplift and erosion during the main hydrocarbon accumulation period in the research area include: stratigraphic trend extrapolation, vitrinite reflectance Ro method, apatite fission track AFT method, or sonic transit time Δlogt method, or one or a combination of at least two of these methods.

8. A device for predicting the lower limit of permeability depth in sandstone reservoirs, characterized in that, The prediction device includes: The module for obtaining the main hydrocarbon accumulation period determines the main hydrocarbon accumulation period in the study area. The module for obtaining tectonic uplift and erosion data reconstructs the tectonic uplift and erosion data during the main hydrocarbon accumulation period in the study area. The prediction module obtains the lower limit of sandstone reservoir permeability depth based on the relationship between tectonic uplift erosion and critical burial depth. The relationship between the tectonic uplift erosion amount and the critical burial depth is as follows: y=K×e λx In the formula, y is the critical burial depth, x is the amount of tectonic uplift and erosion, K is the lithological parameter, and λ is the attenuation coefficient.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and a memory communicatively connected to said at least one processor; The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the method for predicting the lower limit of permeability depth in sandstone reservoirs according to any one of claims 1-7.

10. A computer storage medium, characterized in that, The computer storage medium stores computer-executable instructions, which, when executed by a processor, implement the method for predicting the lower limit of permeability depth in sandstone reservoirs as described in any one of claims 1-7.

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