A method, device and equipment for stratigraphic division of a fan delta front stratum

Abstract

The application provides a fan delta front formation layer division method, device and equipment, and belongs to the field of formation layer division, aiming to improve the accuracy of formation layer division, the method comprises the following steps: generating an INPEFA curve based on the obtained well logging curve of the to-be-divided formation layer; identifying the first sequence boundary of the to-be-divided formation layer based on the first INPEFA curve; sequentially identifying a plurality of sequence boundaries, and dividing the to-be-divided formation layer into a plurality of layer sections according to the identified sequence boundaries; regenerating a second INPEFA curve based on the well logging curves corresponding to the plurality of layer sections, so as to identify the sequence boundary of the next sequence level of the current sequence level; repeating the previous step until the second sequence boundary of the preset sequence level is identified; dividing a plurality of second sequence formation layers based on the second sequence boundary, and obtaining the sand-mud ratio curve of each second sequence formation layer; and dividing the to-be-divided formation layer into a plurality of small-layer-level formation units according to the sand-mud ratio curve.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of stratum division, and particularly relates to a stratum division method, device and equipment for a fan delta front stratum. BACKGROUND

[0002] In oil and gas field exploration and development, stratum division is usually performed by identifying cycles through well logging curves. However, for a fan delta front stratum, it is difficult to identify cycle information from the stratum due to sparse seismic well network, fast change of sand and mud, few marker beds and serious tooth of well logging curves, which results in poor stratum division effect and affects oil and gas development. SUMMARY

[0003] Therefore, the present application aims to provide a stratum division method, device and equipment for a fan delta front stratum to solve the problem of poor stratum division effect for the fan delta front stratum and affect oil and gas development.

[0004] In a first aspect, the present application provides a stratum division method for a fan delta front stratum, which comprises the following steps.

[0005] Step 1: generating a first frequency spectrum attribute trend analysis curve based on obtained well logging curves of a to-be-divided stratum; wherein the well logging curves at least include a natural gamma curve;

[0006] Step 2: identifying a first sequence boundary of the to-be-divided stratum based on the first frequency spectrum attribute trend analysis curve; wherein the first sequence boundary is a sequence boundary with the highest sequence level in the to-be-divided stratum;

[0007] Step 3: starting from the first sequence boundary, sequentially identifying a plurality of sequence boundaries in order of sequence levels, and performing the following steps when each sequence boundary is identified: dividing the to-be-divided stratum into a plurality of layer segments based on the current identified sequence boundary, and regenerating a second frequency spectrum attribute trend analysis curve based on well logging curves corresponding to the plurality of layer segments, so as to identify a sequence boundary of a next sequence level of the current sequence level through the second frequency spectrum attribute trend analysis curve; wherein the sequence levels of different layer segments are the same;

[0008] Step 4: repeating Step 3 until a second sequence boundary of a preset sequence level is identified; wherein the sequence level of the second sequence boundary is lower than that of the first sequence boundary;

[0009] Step 5: dividing a plurality of second sequence strata based on the second sequence boundary, and obtaining a sand and mud ratio curve of each second sequence stratum;

[0010] Step 6: dividing the to-be-divided stratum into a plurality of small-level stratum units according to the sand and mud ratio curve.

[0011] Furthermore, the step of generating a first spectral attribute trend analysis curve based on the acquired well logging curves of the formation to be divided includes:

[0012] The logging curves were processed using maximum entropy spectrum analysis to obtain the estimated maximum entropy spectrum values ​​at each formation depth.

[0013] Based on the maximum entropy spectral analysis estimate and the true value of the natural gamma curve, the data difference at each formation depth is determined.

[0014] Based on the data differences at multiple formation depth locations, a data difference curve is constructed;

[0015] The data difference curve is mathematically integrated using the complex Simpson integral formula to obtain the first spectral attribute trend analysis curve.

[0016] Further, the step of regenerating a second spectral attribute trend analysis curve based on the logging curves corresponding to multiple layers, so as to identify the sequence boundary of the next sequence level of the current sequence level through the second spectral attribute trend analysis curve, includes:

[0017] Based on the natural gamma curve corresponding to each of the aforementioned segments, the second spectral attribute trend analysis curve is regenerated.

[0018] Integrate the trend analysis curves of the second spectral attributes corresponding to multiple layers;

[0019] Based on the integrated second spectral attribute trend analysis curve, the sequence interface of the next sequence level of the current sequence level is identified.

[0020] Furthermore, the logging curve also includes a resistivity curve; when the identified sequence interface has a sequence level of four, the method further includes:

[0021] Based on the natural gamma curve and the resistivity curve, the mudstone marker layer interface is determined;

[0022] The sequence interface identification results were verified based on the depth of the mudstone marker layer interface and the depth of the fourth-order sequence interface.

[0023] Further, obtaining the sand-to-mud ratio curve for each of the sequence strata includes:

[0024] Based on the natural gamma curves of each second sequence stratum, the sand-mud ratio curves are generated using the following formula:

[0025] RSASH = (GR max -GR) / (GR-GRmin )

[0026] Where RSASH represents the sand-to-soil ratio at the current depth, GR represents the natural gamma curve value at the current depth, and GR max GR represents the maximum value of the natural gamma curve. min This represents the minimum value of the natural gamma curve.

[0027] Furthermore, the step of dividing the strata to be divided into multiple smaller stratigraphic units based on the sand-mud ratio curve includes:

[0028] A low-pass filtering algorithm based on fast Fourier transform is used to smooth the sand-to-mud ratio curve.

[0029] The depth value corresponding to the low point of the smoothed sand-mud ratio curve is used as the sub-layer interface to divide the strata to be divided into multiple sub-layer level stratigraphic units.

[0030] Further, the step of processing the well logging curves using maximum entropy spectrum analysis to obtain the maximum entropy spectrum analysis estimate for each formation depth includes:

[0031] For the natural gamma curve, the following formula is used to perform linear prediction of the data sequence to obtain the maximum entropy spectral analysis estimate:

[0032]

[0033] Among them, y n * The maximum entropy spectral analysis estimate is y. n-j d represents the true value of the data point. j is the prediction coefficient.

[0034] Further, the step of identifying the first sequence boundary of the strata to be delineated based on the first spectral attribute trend analysis curve includes:

[0035] Determine the maximum or minimum value of the first spectral attribute trend analysis curve;

[0036] The depth position corresponding to the maximum or minimum value is used as the first layer sequence interface.

[0037] A second aspect of the present invention provides a stratigraphic delineation device for fan delta front strata, the device comprising:

[0038] A generation module is used to generate a first spectral attribute trend analysis curve based on the obtained well logging curves of the formation to be divided; wherein the well logging curves include at least a natural gamma curve;

[0039] The first identification module is used to identify the first sequence boundary of the strata to be divided based on the first spectral attribute trend analysis curve; wherein, the first sequence boundary is the sequence boundary with the highest sequence level in the strata to be divided.

[0040] The second identification module is used to identify multiple sequence interfaces sequentially from the first sequence interface according to the order of sequence level, and to perform the following steps when each sequence interface is identified: based on the currently identified sequence interface, the strata to be divided are divided into multiple segments; based on the well logging curves corresponding to the multiple segments, a second spectral attribute trend analysis curve is regenerated, so as to identify the next sequence interface of the current sequence level through the second spectral attribute trend analysis curve; wherein, the sequence level of different segments is the same;

[0041] The repeating module is used to repeat the steps performed by the second identification module until a second hierarchical interface with a preset hierarchical level is identified; wherein, the hierarchical level of the second hierarchical interface is lower than that of the first hierarchical interface.

[0042] The partitioning module is used to partition multiple second-sequence-level sequence strata based on the second sequence interface, and obtain the sand-mud ratio curve of each sequence stratum; according to the sand-mud ratio curve, the strata to be partitioned are divided into multiple smaller-level stratigraphic units.

[0043] The stratigraphic division device and the stratigraphic division method for the aforementioned fan delta front strata have the same advantages over the prior art, and will not be elaborated here.

[0044] A third aspect of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executed, implements the steps in the stratigraphic division method for fan delta front strata as described in the first aspect above.

[0045] The electronic device and the aforementioned stratigraphic division method have the same advantages over the prior art, and will not be elaborated here.

[0046] Compared with existing technologies, the stratigraphic division method for fan delta front strata described in this invention has the following advantages:

[0047] The stratigraphic delineation method for fan delta front strata provided by this invention includes: Step 1, generating a first spectral attribute trend analysis curve based on the obtained well logging curves of the strata to be delineated; wherein the well logging curves include at least a natural gamma curve; Step 2, identifying a first sequence boundary of the strata to be delineated based on the first spectral attribute trend analysis curve; wherein the first sequence boundary is the sequence boundary with the highest sequence level in the strata to be delineated; Step 3, starting from the first sequence boundary, identifying multiple sequence boundaries sequentially according to the order of sequence level, and performing the following steps when identifying each sequence boundary: delineating the strata to be delineated based on the currently identified sequence boundary. The sequence is divided into multiple segments. Based on the logging curves corresponding to the multiple segments, a second spectral attribute trend analysis curve is regenerated to identify the sequence interface of the next sequence level of the current sequence level. The sequence levels of different segments are the same. Step 4: Repeat step 3 until the second sequence interface of the preset sequence level is identified. The sequence level of the second sequence interface is lower than that of the first sequence interface. Step 5: Based on the second sequence interface, multiple second sequence strata are divided, and the sand-mud ratio curve of each second sequence strata is obtained. Step 6: According to the sand-mud ratio curve, the strata to be divided are divided into multiple stratigraphic units of smaller levels.

[0048] Therefore, this invention employs spectral trend analysis technology to construct spectral attribute trend analysis curves for fan delta front strata. After delineating the first-order sequence stratigraphy, the strata are segmented according to the sequence boundary, and a new spectral attribute trend analysis curve is obtained for each segment. Thus, by performing separate spectral attribute trend analysis on each sequence-level strata, the severe serration of the curves and the difficulty in identifying cycle information when using the entire attribute trend analysis curve for multi-level sequence stratigraphy are avoided, thereby improving the accuracy of stratigraphic delineation. At the same time, using the sand-mud ratio curve for sub-layer stratigraphic delineation is more accurate than using spectral attribute trend analysis. Therefore, by combining spectral attribute trend analysis technology and sand-mud ratio curve analysis, the sub-layer stratigraphic delineation becomes more accurate. Attached Figure Description

[0049] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0050] Figure 1 This invention provides a step flowchart of a stratigraphic division method for a fan delta front strata according to an embodiment of the present invention.

[0051] Figure 2This invention provides a step flowchart of a stratigraphic division method for a fan delta front strata according to another embodiment of the present invention;

[0052] Figure 3 This diagram illustrates the sub-segments, oil groups, and sand groups delineated from the natural gamma curve, resistivity curve, PEFA curve, and INPEFA curve of a single well in an embodiment of the present invention.

[0053] Figure 4 This diagram illustrates the classification of oil-bearing formations using INPEFA curves within the sub-sections of wells L12 and L13.

[0054] Figure 5 This diagram illustrates the classification of oil-bearing formations using INPEFA curves within wells L12 and L13.

[0055] Figure 6 This diagram illustrates the sub-strata division within the sand group in wells L12 and L13, showing the sand-mud ratio curves.

[0056] Figure 7 This diagram illustrates the structure of a stratigraphic division device for a fan delta front strata provided in an embodiment of the present invention. Detailed Implementation

[0057] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0058] In related technologies, stratigraphic correlation is usually carried out by comparing resistivity curves, verifying with other curves, or searching for patterns in electrical logging curves by analyzing sand body types and rhythms to conduct stratigraphic correlation.

[0059] However, for sandstone and mudstone formations, mudstone has a wider distribution range and greater stability than sandstone. For formations with sparse seismic well networks, rapid sand-mudstone changes, few marker layers, and severely serrated logging curves, the severe serration of logging curves makes it difficult to identify cycle information. The use of logging curves to identify cycles for formation division is ambiguous and greatly affected by human factors. Poor formation division results in poor injection-production correspondence in oil fields, affecting oil and gas development.

[0060] Therefore, INPEFA (Integrated Prediction Error Filter Analysis) technology is commonly used to avoid human influence. However, existing INPEFA technology is based on the fact that different sequence levels correspond to different trend inflection points, and the sequence boundaries of multiple sequence levels are determined according to the amplitude of curve changes. This can easily lead to similar overall trends in some areas, resulting in mismatches between sequence levels and affecting the accuracy of stratigraphic delineation. This is especially true for strata in the fan delta front, where the sparse seismic well network, rapid sand-slurry changes, few marker beds, and severe serration of logging curves make accurate and efficient stratigraphic delineation difficult.

[0061] In view of this, the present invention provides a method, apparatus, and equipment for stratigraphic division of strata at the front of a fan delta. After identifying a sequence boundary at each sequence level, the strata are divided into multiple segments. Based on the logging curves of each segment, an INPEFA curve is regenerated to identify the sequence boundary at the next sequence level, accurately dividing sequence boundaries from level one to level five. Simultaneously, considering the low accuracy of INPEFA technology in subdivision, after dividing the fifth-level sequence, a sand-to-mud ratio curve is used to further subdivide the fifth-level sequence strata, thereby dividing multiple sub-level stratigraphic units. Thus, by identifying sequence boundaries at each level of the strata to be divided and using the sand-to-mud ratio curve to identify sub-level boundaries, the purpose of accurate stratigraphic division is achieved.

[0062] The following will describe in detail, with reference to the accompanying drawings and embodiments, a stratigraphic method, apparatus and equipment for dividing strata at the front of a fan delta provided by the present invention.

[0063] Example 1

[0064] Reference Figure 1 , Figure 1 The following is a flowchart illustrating the steps of a stratigraphic division method for a fan delta front strata provided by an embodiment of the present invention: Figure 1 As shown, the method includes:

[0065] Step S101: Based on the obtained well logging curves of the formation to be divided, generate the first spectral attribute trend analysis curve.

[0066] The logging curves mentioned above include at least the natural gamma ray curve. In oil and gas field exploration, various logging curves are commonly used, such as natural gamma ray curves, resistivity curves, and sonic curves. Among these, the natural gamma ray curve contains rich stratigraphic information and can clearly reflect the lithological fabric of the strata. Therefore, the natural gamma ray curve is often used to identify multi-level cycles in the formation and to divide the strata.

[0067] In this embodiment of the invention, the first spectral attribute trend analysis curve is the spectral attribute trend analysis curve of the entire formation to be divided obtained from the well logging curve, and the initial division of the formation is carried out based on the spectral attribute trend analysis curve of the entire formation.

[0068] Among them, the spectral attribute trend curve, namely the INPEFA curve, is a curve that reflects the sedimentary cycle information in the strata. Generally, the maximum entropy spectrum analysis estimate is obtained by the maximum entropy spectrum analysis of the natural gamma curve. Then, the difference between the true value and the estimated value of the natural gamma curve is used to obtain the data difference curve, and then the INPEFA curve is obtained by integrating the data difference curve.

[0069] In some embodiments, well logging data can be directly input into the Direct software, and the INPEFA curve can be directly obtained through the INPEFA curve generation function of the Direct software.

[0070] Step S102: Based on the first spectral attribute trend analysis curve, identify the first sequence boundary of the strata to be divided.

[0071] The first sequence interface is the sequence interface with the highest sequence level in the strata to be divided.

[0072] Specifically, the cyclic characteristics are more pronounced in the spectral attribute trend analysis curves, and stratigraphic division is usually based on the trend changes of the curves. INPEFA curves exhibit two trend forms for identifying cyclic development characteristics: positive and negative trends. In other words, there are two types of inflection points for identifying sequence boundaries: positive and negative inflection points. Generally, a positive trend curve shows an increasing value from left to right, with the curve rising from left to right, representing a subsequent gradual wetting process due to water transgression; a negative trend curve shows a decreasing value from right to left, with the curve falling from right to left, representing a subsequent gradual drying process due to water retreat. The inflection point between the positive and negative trends indicates a sequence boundary or a characteristic interface within a sequence. Furthermore, trend inflection points at different levels indicate isochronous interfaces at different sequence levels. Therefore, the depth value corresponding to the inflection point of the spectral attribute trend analysis curve can be identified as a sequence boundary, thus enabling stratigraphic division.

[0073] In this embodiment of the invention, the division of strata requires the identification of sequence boundaries at multiple sequence levels in order to further subdivide the strata. Therefore, after identifying the sequence boundaries based on the overall INPEFA curve of the strata, the strata are further divided into segments, and the identification of secondary sequence boundaries is carried out again until the required sequence level strata are identified. Therefore, after the highest level sequence boundary is identified, steps S103-S104 are executed.

[0074] Step S103: Starting from the first sequence interface, multiple sequence interfaces are identified sequentially according to the order of sequence level. When a sequence interface is identified, the following steps are performed: Based on the currently identified sequence interface, the strata to be divided are divided into multiple segments. Based on the well logging curves corresponding to the multiple segments, a second spectral attribute trend analysis curve is regenerated to identify the next sequence interface of the current sequence level through the second spectral attribute trend analysis curve.

[0075] In this invention, different sequences share the same sequence level. Specifically, after identifying the first sequence interface, multiple sequence interfaces are identified sequentially in descending order of sequence level. There may be multiple sequence interfaces of the same sequence level, or there may be only one. In this embodiment, sequence interface identification relies on INPEFA curves. Therefore, upon identifying a sequence interface, which is the next sequence level sequence interface to be determined, the formation is divided into multiple segments based on the currently identified sequence interface. Based on the top and bottom positions of each segment, well logging curves are extracted to generate a separate INPEFA curve for that segment. Then, the sequence interface within each segment can be identified based on the corresponding INPEFA curve.

[0076] In some embodiments, to facilitate the division of layers, after obtaining the INPEFA curves of each layer segment, the INPEFA curves can be integrated to identify the sequence interface of the next sequence level based on the integrated INPEFA curves.

[0077] Step S104: Repeat step S103 until the second-level interface of the preset level is identified.

[0078] The second sequence boundary has a lower sequence level than the first sequence boundary. Stratigraphic division typically involves dividing strata into multiple sequence levels. Generally, the division process divides strata into first to fifth-order sequence strata. Therefore, when identifying sequence boundaries, the process continues until a fifth-order sequence boundary is identified, thus completing the strata division.

[0079] In this embodiment of the invention, in order to achieve stratigraphic division at the sub-layer level, after dividing the first to fifth order sequence strata, the sub-layer interface is identified based on the divided fifth order sequence strata. Therefore, steps S105-S106 are executed to achieve stratigraphic division at the sub-layer level.

[0080] Step S105: Based on the second sequence interface, multiple second sequence strata are divided, and the sand-mud ratio curve of each second sequence strata is obtained.

[0081] Step S106: Based on the sand-mud ratio curve, the strata to be divided are divided into multiple stratigraphic units of smaller levels.

[0082] Specifically, since the accuracy of using INPEFA curves for sub-layer interface identification is not high, this embodiment of the invention uses sand-mud ratio curves for sub-layer sequence interface identification, wherein the sand-mud ratio curves are based on data acquired from natural gamma curves. Since the sub-layer interface identification is within a fifth-order sequence stratigraphy, the natural gamma curve of each fifth-order sequence stratigraphy is acquired. Based on the natural gamma curves, the sand-mud ratio curve of each fifth-order sequence stratigraphy is determined. Then, multiple sub-layers are divided within each fifth-order sequence stratigraphy, thereby dividing the strata to be divided into multiple sub-layer level stratigraphic units.

[0083] In this embodiment of the invention, after identifying the highest-level sequence boundary using INPEFA technology, the strata are initially divided based on the sequence boundary. Then, INPEFA curves corresponding to each sequence stratum are regenerated for the next level of sequence boundary, until a second sequence boundary at the preset sequence level is determined. Thus, by performing separate spectral attribute trend analysis on each sequence stratum at each sequence level, the severe serration of the curve, which makes it difficult to identify cyclic information, is avoided when using the entire attribute trend analysis curve for multi-level sequence strata division, thereby improving the accuracy of stratigraphic division. At the same time, using the sand-mud ratio curve for small-level stratigraphic division is more accurate than using spectral attribute trend analysis. Therefore, by combining spectral attribute trend analysis technology and sand-mud ratio curve analysis, the division of small-level stratigraphic layers becomes more accurate.

[0084] Reference Figure 2 , Figure 2 A flowchart illustrating the steps of a stratigraphic division method for a fan delta front strata according to another embodiment of the present invention is shown, as follows: Figure 2 As shown, the method includes:

[0085] Step S201: The logging curves are processed using maximum entropy spectrum analysis to obtain the estimated maximum entropy spectrum values ​​at each formation depth.

[0086] Maximum entropy spectral analysis is a spectral analysis method that extrapolates the autocorrelation function according to the maximum information entropy criterion, thereby improving the resolution of spectral estimation. Specifically, for natural gamma curves, the following formula is used to perform linear prediction of the data sequence to obtain the maximum entropy spectral analysis estimate for each formation depth:

[0087]

[0088] Among them, y n * The maximum entropy spectral analysis estimate is y. n-jd represents the true value of the data point. j is the prediction coefficient.

[0089] Step S202: Based on the maximum entropy spectrum analysis estimate and the true value of the natural gamma curve, determine the data difference at each formation depth location.

[0090] Step S203: Construct a data difference curve based on the data differences at multiple stratigraphic depth locations.

[0091] After obtaining the maximum entropy spectrum analysis estimate, prediction error filtering analysis is performed. For each formation depth, the data difference is obtained, which is the difference between the true value of the natural gamma curve at the corresponding depth and the estimate of the maximum entropy spectrum analysis.

[0092] After obtaining the data difference at each stratigraphic depth, a data difference curve, namely the PEFA (Prediction Error Filter Analysis) curve, can be constructed based on the data difference. The data difference curve is an irregular toothed curve that varies along a vertical line. It can serve as an indicator for interpreting stratigraphic continuity. Negative peaks represent possible sequence boundaries, positive peaks represent possible floodplains, and peaks of different sizes indicate isochronous boundaries of different sizes.

[0093] Step S204: Perform mathematical integration on the data difference curve using the complex Simpson integral formula to obtain the first spectral attribute trend analysis curve.

[0094] Although the data difference curve can reflect the stratigraphic characteristics, it is usually severely serrated and the peak position is difficult to identify. Therefore, after obtaining the PEFA curve, the PEFA curve is integrated to obtain the INPEFA curve with obvious trend changes.

[0095] In some embodiments, the above process can be implemented using direct software. The acquired logging data, such as natural gamma data, is input into the direct software, and the INPEFA curve of the formation to be divided is directly obtained through the INPEFA curve generation function of the direct software.

[0096] Step S205: Based on the first spectral attribute trend analysis curve, identify the first sequence boundary of the strata to be divided.

[0097] The first sequence interface is the sequence interface with the highest sequence level in the strata to be divided.

[0098] Specifically, the maximum or minimum value of the first spectral attribute trend analysis curve is determined; the depth location corresponding to the maximum or minimum value is used as the first sequence boundary of the strata to be divided. The inflection point in the INPEFA curve is the extreme point; therefore, the depth location corresponding to the maximum or minimum point in the INPEFA curve is used as the sequence boundary.

[0099] In this embodiment of the invention, considering the potential errors in identifying secondary cycles using the overall curve, the sequence boundaries of the strata are identified in a hierarchical manner. That is, after identifying the sequence boundary at the highest sequence level in the current stratum, multiple segments are divided based on the sequence boundary, and the next level sequence boundary is identified through the INPEFA curve corresponding to each segment. This process is repeated until the fifth-level sequence boundary is identified. For the specific hierarchical identification steps, please refer to steps S206-S207.

[0100] In particular, due to the significant differences in stratigraphic development in different regions, the sequence boundary with the highest sequence level in the strata to be divided is not necessarily a first-order sequence boundary. For example, in the strata of the fan delta front, the highest sequence strata level is generally the third level, so the first sequence boundary is a third-order sequence boundary. However, in other stratigraphic locations, the highest sequence strata level is the second level, so the first sequence boundary is a second-order sequence boundary.

[0101] Step S206: Starting from the first hierarchical interface, multiple hierarchical interfaces are identified sequentially according to the hierarchical level. Steps S207-S208 are executed each time a hierarchical interface is identified.

[0102] Step S207: Based on the currently identified sequence interface, the strata to be divided are divided into multiple segments, and the second spectral attribute trend analysis curve is regenerated based on the natural gamma curve corresponding to each segment.

[0103] Step S208: Integrate the second spectral attribute trend analysis curves corresponding to multiple layers, and based on the integrated second spectral attribute trend analysis curves, identify the sequence interface of the next layer of the current sequence level.

[0104] In this system, different segments share the same sequence level. In the first identification, the currently identified sequence interface is the first sequence interface. In the second identification, the currently identified sequence interface is the sequence interface of the next lower sequence level after the first sequence interface, and so on. That is, the currently identified sequence interface is the lowest sequence level among the currently identified sequence interfaces. For example, if a first-level, second-level, and third-level sequence interface are identified, multiple segments are divided based on the third-level sequence interface to obtain multiple third-level sequence strata.

[0105] After dividing the formation into multiple segments with the same sequence level, the INPEFA curve is reconstructed from the well logging curves for each segment to obtain the corresponding INPEFA curve. This refines the INPEFA curve and allows for the identification of the next sequence level sequence boundary in the corresponding sequence formation.

[0106] For example, after dividing the strata to be subdivided into multiple third-order sequence strata, the natural gamma curve corresponding to each third-order sequence stratum is obtained. Based on the natural gamma curve of the segment, maximum entropy spectral analysis is performed to obtain the estimated value of the maximum entropy spectral analysis. Then, based on the true value of the natural gamma curve and the estimated value of the maximum entropy spectral analysis, a PEFA curve is generated. Then, the INPEFA curve corresponding to the segment is obtained by integration. Thus, by analyzing the INPEFA curve of each segment separately, the next sequence boundary in the segment can be identified. This avoids the error of using the overall INPEFA curve for multi-level sequence boundary identification and improves the accuracy of multi-level sequence boundary identification.

[0107] In some embodiments, in order to simultaneously identify the next-level sequence interface of multiple segments, after regenerating the INPEFA curve corresponding to each segment, the INPEFA curves of multiple segments are integrated, so as to simultaneously identify the next-level sequence interface of multiple segments based on the integrated INPEFA curve.

[0108] For example, if there is only one first sequence interface, after dividing the strata into two segments based on the first sequence interface, the INPEFA curves corresponding to the two segments are regenerated, namely INPEFA curve 1 and INPEFA curve 2. INPEFA curve 1 and INPEFA curve 2 are then integrated into INPEFA curve 3. Based on INPEFA curve 3, the next sequence interface of the first sequence interface is identified.

[0109] In some embodiments, after dividing into multiple segments, the logging data of the corresponding segments can be input into the Direct software to directly generate the INPEFA curve corresponding to each segment, and then the sequence interface can be identified.

[0110] In some embodiments, since the primary objective of oil and gas field exploration and development is to identify oil-bearing formations, accurate identification of oil-bearing formation interfaces is particularly important. Given that in multi-level sequence stratigraphy, third-order sequence stratigraphy represents oil-bearing formations, fourth-order sequence stratigraphy represents oil-bearing formations, and fifth-order sequence stratigraphy represents sand formations, the division of fourth- and fifth-order sequence stratigraphy needs to be more precise during the sequence stratigraphic division process.

[0111] Therefore, after the fourth-order sequence is delineated, the fourth-order sequence interface can be verified to ensure the accuracy of the oil group delineation; specifically, the mudstone marker layer interface is determined based on the natural gamma curve and the resistivity curve; the identification results are verified based on the depth of the mudstone marker layer interface and the depth of the fourth-order sequence interface.

[0112] In this process, the depth value corresponding to the low point shared by the natural gamma curve and resistivity curve is identified as the mudstone marker layer interface. The depth value of the identified marker layer interface is compared with the depth value of the fourth-order sequence interface to verify the accuracy of the current division result.

[0113] Step S209: Repeat steps S207-S208 until the second-level interface of the preset level is identified.

[0114] In this design, the sequence level of the second sequence interface is lower than that of the first sequence interface. The preset sequence level is determined according to requirements. If only a third-level sequence strata need to be identified, the preset sequence level is third; if a complete stratigraphic division is required, the preset sequence level is fifth. This invention does not impose specific limitations and depends on the actual situation. Since stratigraphic division involves dividing the strata into multiple sequence levels, at least two sequence levels must be identified during the division process. Therefore, the sequence level of the second sequence interface is lower than that of the first sequence interface.

[0115] In this embodiment of the invention, a complete division of the strata requires further subdivision at the sub-layer level. Therefore, after identifying the fifth-order sequence boundary, steps S210-S211 are executed to complete the sub-layer level strata division.

[0116] Step S210: Based on the second sequence interface, multiple second sequence strata are divided, and the sand-mud ratio curve of each second sequence strata is obtained.

[0117] Specifically, based on the fifth-order sequence boundaries identified by the INPEFA curve, the strata to be delineated are divided into multiple fifth-order sequence strata. For each fifth-order sequence stratum, the sand-mud ratio curve is obtained for stratigraphic delineation.

[0118] The method for obtaining the sand-to-mud ratio curve is as follows: based on the natural gamma curve of each second sequence stratum, the sand-to-mud ratio curve is generated using the following formula:

[0119] RSASH = (GR max -GR) / (GR-GR min )

[0120] Where RSASH represents the sand-to-soil ratio at the current depth, GR represents the natural gamma curve value at the current depth, and GRmax GR represents the maximum value of the natural gamma curve. min This represents the minimum value of the natural gamma curve.

[0121] Step S211: Based on the sand-mud ratio curve, the strata to be divided are divided into multiple stratigraphic units of smaller levels.

[0122] A low-pass filtering algorithm based on Fast Fourier Transform is used to smooth the sand-mud ratio curve. The depth values ​​corresponding to the low points of the smoothed sand-mud ratio curve are used as sub-layer boundaries to divide the strata to be divided into multiple sub-layer stratigraphic units. This completes the sub-layer boundary division.

[0123] The low-pass filtering algorithm using Fast Fourier Transform can filter out high-frequency signals in the curve, thereby smoothing the curve. In this embodiment of the invention, the calculated sand-to-mud ratio curve data can be imported into Origin software, and the curve smoothing tool can be called, selecting the low-pass filtering algorithm as the method to complete the smoothing process of the sand-to-mud ratio curve.

[0124] This invention employs INPEFA technology, utilizing the natural gamma curve from well logging curves to generate INPEFA curves. Sequence boundaries are identified using these INPEFA curves. During the identification process, a hierarchical identification method is used. After identifying the sequence boundaries, the formation is divided into multiple segments based on these boundaries. The INPEFA curve for each segment is reconstructed for sequence boundary identification. This approach, by performing separate spectral attribute trend analysis on each sequence level, avoids the severe serration of curves and difficulty in identifying cyclic information when using a whole attribute trend analysis curve for multi-level sequence strata division, thus improving the accuracy of strata division. Simultaneously, using sand-mud ratio curves for small-level strata division is more accurate than using spectral attribute trend analysis. Therefore, the combination of spectral attribute trend analysis and sand-mud ratio curve analysis makes small-level strata division more accurate.

[0125] The above process will be illustrated with a specific example below:

[0126] From the well logging data of the fan delta front strata, wells L12 and L13 were selected for stratigraphic delineation of the strata to be delineated.

[0127] First, well logging curves for identifying sandstone and mudstone formations in the Sha-3 section were selected, including natural gamma-ray curves and resistivity curves. Prediction error filtering analysis was performed on the natural gamma-ray curves of wells L12 and L13 to obtain the PEFA curves.

[0128] Then, based on the PEFA curve, mathematical integration is performed using the composite Simpson integral formula to obtain the INPEFA curve, which transforms the original PEFA curve with a less obvious trend into the INPEFA curve, thereby making the trend more obvious.

[0129] Next, the depths corresponding to the positive and negative inflection points of the INPEFA curve are selected as the third-level sequence interface, such as... Figure 3 As shown, Figure 3 In this embodiment of the invention, the natural gamma ray curve, resistivity logging curve, PEFA curve, and INPEFA curve of a single well are used to divide the well into sub-sections, oil groups, and sand groups; according to... Figure 3 The INPEFA curve shown in the figure reveals that the depth point of the third-order sequence interface is at a depth of approximately 2875m.

[0130] Subsequently, based on the defined third-order sequence boundary, the strata were divided into two third-order sequence strata, namely, the depth point E from the upper bottom of the curve to the third-order sequence boundary. S 3 Top-E S 3. The bottom of the upper segment, and the depth point of the third-level sequence interface to the lower bottom E of the curve. S 3 Upper section bottom-E S 3. Based on the natural gamma curves at the corresponding depth positions of the two curves, INPEFA curve 2 and INPEFA curve 3 are generated respectively. After integrating INPEFA curve 2 and INPEFA curve 3, the oil group-level INPEFA curve is obtained to identify the fourth-order sequence interface.

[0131] After identifying the fourth-order sequence boundaries, the strata to be divided are further subdivided into multiple fourth-order sequence strata based on these boundaries. For each fourth-order sequence stratum, the top and bottom of the stratum are determined to establish the well logging curves for that stratum. Figure 4 As shown, based on the subsections E in wells L12 and L13 S 3 Top-E S The upper section of the bottom, the generated INPEFA curve, and the identified fourth-level hierarchical interface.

[0132] Then, based on the natural gamma curve of each fourth-order sequence stratum, the corresponding INPEFA curve is generated. The INPEFA curves corresponding to multiple fourth-order sequence strata are then integrated into sandstone-level INPEFA curves. Based on the delineated fifth-order sequence boundaries, the strata to be delineated can be divided into multiple fifth-order sequence strata, such as... Figure 5 As shown, it illustrates the multiple fifth-level sequence interfaces identified based on the regenerated INPEFA curves.

[0133] Based on the sedimentary characteristics of the study area, it was found that thick mudstone layers were developed at the top of the oil group. In well L12, based on the trend of GR and RT curves, it can be determined that the natural gamma and resistivity curves at 2500m are both low, which is the corresponding marker layer, to verify whether the inflection point of the INPEFA curve is a sequence boundary.

[0134] Subsequently, for each fifth-order sequence stratigraphy, the maximum and minimum natural gamma values ​​are determined based on the corresponding natural gamma curve. Then, the sand-mud ratio curve is generated based on the ratio of the difference between the maximum natural gamma value and the corresponding depth point to the difference between the corresponding depth point and the minimum natural gamma value of the target segment.

[0135] Finally, the generated sand-to-sludge ratio curve is filtered out using a low-pass filter algorithm based on Fast Fourier Transform to remove high-frequency signals, resulting in a smooth sand-to-sludge ratio curve, as shown below. Figure 6 As shown, Figure 6 The formation interfaces at the sub-layer level in wells L12 and L13 are shown respectively. After filtering by a low-pass filtering algorithm, the curves are smoother than the original sand-mud ratio curves. The low points in the smoothed sand-mud ratio curves are used as sub-layer interfaces, dividing the formation to be divided into multiple sub-layer level formation units.

[0136] Example 2

[0137] Reference Figure 7 , Figure 7 This invention illustrates a stratigraphic division device for fan delta front strata provided by an embodiment of the present invention, such as... Figure 7 As shown, the device includes:

[0138] The generation module 301 is used to generate a first spectral attribute trend analysis curve based on the obtained well logging curves of the formation to be divided; wherein, the well logging curves include at least a natural gamma curve;

[0139] The first identification module 302 is used to identify the first sequence interface of the strata to be divided based on the first spectral attribute trend analysis curve; wherein, the first sequence interface is the sequence interface with the highest sequence level in the strata to be divided.

[0140] The second identification module 303 is used to identify multiple sequence interfaces sequentially from the first sequence interface according to the order of sequence level, and to perform the following steps when identifying a sequence interface: based on the currently identified sequence interface, the strata to be divided are divided into multiple segments; based on the well logging curves corresponding to the multiple segments, a second spectral attribute trend analysis curve is regenerated, so as to identify the next sequence interface of the current sequence level through the second spectral attribute trend analysis curve; wherein, the sequence level of different segments is the same;

[0141] The repeating module 304 is used to repeat the steps performed by the second identification module 303 until a second hierarchical interface with a preset hierarchical level is identified; wherein, the hierarchical level of the second hierarchical interface is lower than that of the first hierarchical interface.

[0142] The partitioning module 305 is used to partition multiple second-sequence-level sequence strata based on the second sequence interface and obtain the sand-mud ratio curve of each sequence stratum; and to divide the strata to be partitioned into multiple smaller-level stratigraphic units according to the sand-mud ratio curve.

[0143] In some feasible embodiments, the generation module 301 includes:

[0144] The processing module is used to process the well logging curves using maximum entropy spectrum analysis to obtain the maximum entropy spectrum analysis estimate for each formation depth.

[0145] The determination module is used to determine the data difference at each formation depth location based on the maximum entropy spectrum analysis estimate and the true value of the natural gamma curve.

[0146] The module is used to construct data difference curves based on data differences at multiple stratigraphic depth locations;

[0147] The first generation submodule is used to perform mathematical integration on the data difference curve using the complex Simpson integral formula to obtain the first spectral attribute trend analysis curve.

[0148] In some feasible embodiments, the second identification module 303 includes:

[0149] The second generation submodule is used to regenerate the second spectral attribute trend analysis curve based on the natural gamma curve corresponding to each of the layers.

[0150] The integration module is used to integrate the second spectral attribute trend analysis curves corresponding to multiple layers;

[0151] The identification submodule is used to identify the next level sequence interface of the current sequence interface based on the integrated second spectral attribute trend analysis curve.

[0152] In some feasible embodiments, the apparatus further includes:

[0153] The verification module is used to determine the mudstone marker layer interface based on the natural gamma curve and the resistivity curve; and to verify the identification results based on the depth of the mudstone marker layer interface and the depth of the fourth-order sequence interface.

[0154] Based on the same inventive concept, embodiments of the present invention also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the steps in the stratigraphic division method for fan delta front strata as described in any of the above embodiments.

[0155] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0156] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, embodiments of the present invention can take the form of entirely hardware embodiments, entirely software embodiments, or embodiments combining software and hardware aspects. Furthermore, embodiments of the present invention can take the form of computer program products implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0157] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0158] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0159] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1One or more processes and / or boxes Figure 1 Figure 1 The steps of the function specified in one or more boxes.

[0160] Although preferred embodiments of the present invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present invention.

[0161] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element.

[0162] The stratigraphic division method, apparatus, and equipment for the fan delta front provided by the present invention have been described in detail above. Specific examples have been used to illustrate the principle and implementation of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation and application scope based on the idea of ​​the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for stratigraphic division of strata at the front of a fan delta, characterized in that, The method includes: Step 1: Based on the obtained well logging curves of the formation to be divided, generate a first spectral attribute trend analysis curve; wherein, the well logging curves include at least a natural gamma curve; Step 2: Based on the first spectral attribute trend analysis curve, identify the first sequence boundary of the strata to be divided; wherein, the first sequence boundary is the sequence boundary with the highest sequence level in the strata to be divided. Step 3: Starting from the first sequence interface, identify multiple sequence interfaces sequentially according to their sequence level. Upon identifying each sequence interface, perform the following steps: Based on the currently identified sequence interface, divide the strata to be divided into multiple segments; based on the well logging curves corresponding to the multiple segments, regenerate a second spectral attribute trend analysis curve to identify the next sequence interface of the current sequence level; wherein, different segments have the same sequence level. Step 4: Repeat step 3 until a second-level interface with a preset hierarchical level is identified; wherein the hierarchical level of the second-level interface is lower than that of the first-level interface. Step 5: Based on the second sequence boundary, divide multiple second sequence strata and obtain the sand-mud ratio curve for each second sequence strata; Step 6: Based on the sand-mud ratio curve, divide the strata to be divided into multiple stratigraphic units of smaller levels.

2. The stratigraphic division method for the strata of the fan delta front according to claim 1, characterized in that, The generation of the first spectral attribute trend analysis curve based on the obtained well logging curves of the formation to be divided includes: The logging curves were processed using maximum entropy spectrum analysis to obtain the estimated maximum entropy spectrum values ​​at each formation depth. Based on the maximum entropy spectral analysis estimate and the true value of the natural gamma curve, the data difference at each formation depth is determined. Based on the data differences at multiple formation depth locations, a data difference curve is constructed; The data difference curve is mathematically integrated using the complex Simpson integral formula to obtain the first spectral attribute trend analysis curve.

3. The stratigraphic division method for the strata of the fan delta front according to claim 1, characterized in that, The step of regenerating a second spectral attribute trend analysis curve based on the well logging curves corresponding to multiple layers, in order to identify the sequence boundary of the next sequence level of the current sequence level through the second spectral attribute trend analysis curve, includes: Based on the natural gamma curve corresponding to each of the aforementioned segments, the second spectral attribute trend analysis curve is regenerated. Integrate the trend analysis curves of the second spectral attributes corresponding to multiple layers; Based on the integrated second spectral attribute trend analysis curve, the sequence interface of the next sequence level of the current sequence level is identified.

4. The stratigraphic division method for the strata of the fan delta front according to claim 1, characterized in that, The logging curves also include resistivity curves; when the sequence level of the identified sequence interface is fourth level, the method further includes: Based on the natural gamma curve and the resistivity curve, the mudstone marker layer interface is determined; The sequence interface identification results were verified based on the depth of the mudstone marker layer interface and the depth of the fourth-order sequence interface.

5. The stratigraphic division method for the strata of the fan delta front according to claim 1, characterized in that, The process of obtaining the sand-mud ratio curve for each sequence formation includes: Based on the natural gamma curves of each second sequence stratum, the sand-mud ratio curves are generated using the following formula: RSASH=(GR max -GR) / (GR-GR min ) Where RSASH represents the sand-to-soil ratio at the current depth, GR represents the natural gamma curve value at the current depth, and GR max GR represents the maximum value of the natural gamma curve. min This represents the minimum value of the natural gamma curve.

6. The stratigraphic division method for fan delta front strata according to claim 1, characterized in that, The step of dividing the strata to be classified into multiple stratigraphic units of smaller levels based on the sand-mud ratio curve includes: A low-pass filtering algorithm based on fast Fourier transform is used to smooth the sand-to-mud ratio curve. The depth value corresponding to the low point of the smoothed sand-mud ratio curve is used as the sub-layer interface to divide the strata to be divided into multiple sub-layer level stratigraphic units.

7. The stratigraphic division method for the strata of the fan delta front according to claim 2, characterized in that, The process of processing the well logging curves using maximum entropy spectral analysis to obtain the maximum entropy spectral analysis estimate for each formation depth includes: For the natural gamma curve, the following formula is used to perform linear prediction of the data sequence to obtain the maximum entropy spectral analysis estimate: Among them, y n * The maximum entropy spectral analysis estimate is y. n-j d represents the true value of the data point. j is the prediction coefficient.

8. The stratigraphic division method for fan delta front strata according to claim 1, characterized in that, The step of identifying the first sequence boundary of the strata to be delineated based on the first spectral attribute trend analysis curve includes: Determine the maximum or minimum value of the first spectral attribute trend analysis curve; The depth position corresponding to the maximum or minimum value is used as the first layer sequence interface.

9. A stratigraphic division device for fan delta front strata, characterized in that, The device includes: A generation module is used to generate a first spectral attribute trend analysis curve based on the obtained well logging curves of the formation to be divided; wherein the well logging curves include at least a natural gamma curve; The first identification module is used to identify the first sequence boundary of the strata to be divided based on the first spectral attribute trend analysis curve; wherein, the first sequence boundary is the sequence boundary with the highest sequence level in the strata to be divided. The second identification module is used to identify multiple sequence interfaces sequentially from the first sequence interface according to the order of sequence level, and to perform the following steps when each sequence interface is identified: based on the currently identified sequence interface, the strata to be divided are divided into multiple segments; based on the well logging curves corresponding to the multiple segments, a second spectral attribute trend analysis curve is regenerated, so as to identify the next sequence interface of the current sequence level through the second spectral attribute trend analysis curve; wherein, the sequence level of different segments is the same; The repeating module is used to repeat the steps performed by the second identification module until a second hierarchical interface with a preset hierarchical level is identified; wherein, the hierarchical level of the second hierarchical interface is lower than that of the first hierarchical interface. The partitioning module is used to partition multiple second-sequence-level sequence strata based on the second sequence interface, and obtain the sand-mud ratio curve of each sequence stratum; according to the sand-mud ratio curve, the strata to be partitioned are divided into multiple smaller-level stratigraphic units.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes, it implements the steps in the stratigraphic division method for the fan delta front strata as described in any one of claims 1-8.

Images