A method for identifying igneous rock lithology based on ECS element logging

Abstract

The present application relates to a kind of igneous rock lithology identification method based on ECS element logging, the igneous rock lithology identification method is in the layer to be evaluated in research well, the lithology of well wall coring, thin section core depth point of drilled well, conventional logging and ECS element capture logging, determine the large class lithology logging response characteristics;And based on the lithology of well wall coring and thin section core depth point of drilled well, determine the carbonate rock and igneous rock two major lithology identification method and parameter;And for igneous rock lithology, based on the lithology of well wall coring and thin section core depth point, combined with ECS element capture logging and natural gamma ray logging spectrometry, confirm to identify the intrusion rock mainly with diabase and the eruption rock mainly with basalt.The identification method has higher discrimination accuracy, and identification method is relatively simple, is conducive to realizing automatic efficient identification, with good application prospect.

Description

Technical Field

[0001] This invention belongs to the field of petroleum exploration technology and relates to a method for identifying the lithology of igneous rocks, and more particularly to a method for identifying the lithology of igneous rocks based on ECS elemental logging. Background Technology

[0002] With the continuous deepening of lithological oil and gas reservoir exploration, well logging evaluation of igneous reservoirs has become the focus of attention for scholars. Igneous rocks are diverse in type, and can be divided into intrusive rocks and eruptive rocks according to their genesis. According to the SiO2 content, they can be divided into four categories: ultrabasic, basic, intermediate and acidic. Therefore, evaluating the lithology of igneous rocks is a major challenge in well logging evaluation.

[0003] Conventional methods for identifying igneous lithology include the TAS classification chart method, conventional well logging curve cross-plot method, and ECS well logging mineral quantitative calculation method. The currently widely used method is the TAS classification chart method proposed by the International Union of Geological Sciences (IUGS) Igneous Rock Classification Society in 1986. This method establishes a chart based on the total alkali (K2O+Na2O) and SiO2 content, assuming the rock is known to be igneous. However, this method cannot distinguish igneous rocks from other lithologies.

[0004] From the 1970s to the 1990s, foreign scholars such as Sanyal SK, Rigby FA, ​​and Benoit WR used cross-plot analysis of natural gamma, neutron, density, and sonic logging curves to identify lithologies such as rhyolite, basalt, and tuff. In the early 21st century, with breakthroughs in the exploration of igneous rocks in large basins such as the Songliao Basin, Junggar Basin, and Bohai Bay Basin in my country, domestic scholars have also deepened their research on the lithology of igneous rocks. By the 2010s, unconventional logging methods such as ECS and FMI had improved the accuracy of igneous rock lithology identification. The main methods included quantitative mineral calculation based on ECS logging (Zhao Jun et al., Lithology identification method based on ECS logging. Progress in Geophysics, 2015, 30(5):2342-2348) and igneous rock lithology identification based on ECS and FMI imaging data (Li Ning et al., Theory and application of volcanic rock logging interpretation. Petroleum Exploration and Development, 2009, 36(6):683-692).

[0005] Currently, conventional well logging crossplot technology has become an important technique for igneous rock lithology identification. Scholars both domestically and internationally are exploring the use of unconventional logging methods such as ECS elemental logging and imaging logging for igneous rock lithology identification to reduce ambiguity in conventional well logging crossplots. However, due to the highly complex lithology of igneous rocks—which can vary significantly across different regions, phases, and even the same layer—and the differences in intrusion, eruption, and cooling rates, existing technologies struggle to accurately measure the lithology of igneous rocks.

[0006] Well logging lithology identification is fundamental to oil and gas exploration and development, as well as well logging interpretation and evaluation. However, the complexity of lithology poses a challenge to volcanic rock lithology identification. Only high-precision lithology identification can effectively facilitate reservoir well logging evaluation, sedimentary reservoir studies, and reservoir classification. Particularly in deep-water carbonate oil and gas exploration, igneous rock lithology identification is crucial for understanding the impact on reservoirs and their physical properties. Therefore, it is necessary to provide a method for igneous rock lithology identification based on ECS elemental logging. Summary of the Invention

[0007] The purpose of this invention is to provide a method for identifying igneous rock lithology based on ECS elemental logging, and more particularly, to provide a method for identifying igneous rock lithology by using ECS ​​elemental logging and GR energy dispersive spectroscopy logging to analyze elements sensitive to igneous rock lithology and establishing an igneous rock lithology identification formula.

[0008] To achieve this objective, the present invention adopts the following technical solution:

[0009] This invention provides a method for identifying igneous rock lithology based on ECS elemental logging, the method comprising the following steps:

[0010] (1) Obtain the standardized logging curves of the layer to be evaluated in the study well;

[0011] (2) Load the lithology of the wellbore core and thin section core depth points of the layer to be evaluated in the research well, select sample points with obvious logging characteristics, and ensure the accuracy of lithology identification;

[0012] (3) Based on the sample points selected in step (2), determine the two major categories of lithological logging response characteristics according to the sensitive logging curves;

[0013] (4) Using the sensitive logging curves described in step (3), establish neutron-density logging cross plots and Ca-Si logging cross plots. Combine the logging response characteristics of the two major types of lithology, carbonate rocks and igneous rocks, establish the discriminant formula for identification parameters, and obtain the lithology of carbonate rocks and igneous rocks.

[0014] (5) Based on the lithology of the igneous rocks obtained in step (4), and combined with the lithology of the wellbore core and thin section core depth points, an identification chart for intrusive and eruptive rocks is established by combining ECS ​​elemental capture logging and natural gamma ray spectral logging.

[0015] (6) Ignition lithology is identified based on the lithological index parameters of the identification chart obtained in step (5), and intrusive rocks and eruptive rocks are identified.

[0016] The "obtaining standardized logging curves of the layer to be evaluated in the research well" mentioned in step (1) of this invention refers to removing the influence of wellbore enlargement, outliers, and systematic deviations caused by different logging instruments through conventional preprocessing, quality analysis, and standardization methods in the field.

[0017] The step (2) of this invention, "selecting sample points with obvious logging characteristics", refers to performing quality analysis on all sample points, screening out samples with unclear lithological characteristics from wellbore core sampling and blurry thin section lithological observation characteristics, and selecting samples with obvious logging characteristics without the influence of enlargement, so as to ensure the accuracy of lithological identification.

[0018] The "sensitive logging curve" mentioned in step (3) of this invention is obtained by cross-analysis of conventional logging curves and ECS element capture logging curves using two-parameter and three-parameter methods.

[0019] The discriminant of the identification parameter in step (4) of this invention is based on ECS element capture logging, which is only sensitive to rock-forming elements and is not affected by rock pore fluid.

[0020] This invention provides a method for identifying igneous rock lithology based on ECS elemental logging. This method is adaptable to igneous rock lithology identification in complex lithological zones, considering both carbonate rock development and various types of igneous rocks, thus improving the identification quality in complex lithological zones. The igneous rock lithology identification method provided by this invention identifies the lithology of drilled wellbore cores, thin-section core depths, conventional logging, and ECS elemental capture logging in the layers to be evaluated in the research well, determining the logging response characteristics of a large number of lithological classes. Based on the lithology of drilled wellbore cores and thin-section core depths, it determines the identification methods and parameters for two major lithological classes: carbonate rocks and igneous rocks. Furthermore, for igneous rock lithology, based on the lithology of wellbore cores and thin-section core depths, combined with ECS elemental capture logging and natural gamma ray spectral logging, it confirms and identifies intrusive rocks dominated by diabase and extrusive rocks dominated by basalt. The identification method described has high discrimination accuracy and is relatively simple, which is conducive to achieving automatic and efficient identification and has good application prospects.

[0021] Preferably, the logging curves in step (1) include the caliber curve (CAL), the natural gamma logging curve (GR), the natural gamma spectral logging curve, the neutron logging curve (NPHI), the density logging curve (RHOB), and the ECS elemental capture logging curve.

[0022] Preferably, the sensitive logging curve in step (3) includes any one or a combination of at least two of the following: density logging curve RHOB, natural gamma ray spectroscopy logging curve, or ECS element capture logging curve. Typical but non-limiting combinations include the combination of density logging curve RHOB and natural gamma ray spectroscopy logging curve, the combination of density logging curve RHOB and ECS element capture logging curve, the combination of natural gamma ray spectroscopy logging curve and ECS element capture logging curve, or the combination of density logging curve RHOB, natural gamma ray spectroscopy logging curve, and ECS element capture logging curve; preferably, it is a combination of density logging curve RHOB, natural gamma ray spectroscopy logging curve, and ECS element capture logging curve.

[0023] Preferably, the natural gamma ray spectral logging curve includes any one or a combination of at least two of the following: TH spectral logging curve, U spectral logging curve, or K spectral logging curve. Typical but non-limiting combinations include the combination of TH spectral logging curve and U spectral logging curve, the combination of U spectral logging curve and K spectral logging curve, the combination of TH spectral logging curve and K spectral logging curve, or the combination of TH spectral logging curve, U spectral logging curve, and K spectral logging curve; preferably, it is a combination of TH spectral logging curve, U spectral logging curve, and K spectral logging curve.

[0024] Preferably, the ECS element capture logging curve includes any one or at least two combinations of Ca capture logging curves, Si capture logging curves, Fe capture logging curves, Na capture logging curves, or K capture logging curves. Typical but non-limiting combinations include combinations of Ca and Si capture logging curves, combinations of Fe and Na capture logging curves, combinations of Si and K capture logging curves, or combinations of Ca, Si, Fe, Na, and K capture logging curves; preferably, it is a combination of Ca, Si, Fe, Na, and K capture logging curves.

[0025] Preferably, the identification parameters in the discriminant formula of the identification parameters in step (4) are Ca and Si; Ca is the percentage content of Ca element in ECS element capture logging; and Si is the percentage content of Si element in ECS element capture logging.

[0026] From the perspective of rock chemical composition, the main oxides in carbonate rocks are CaO and MgO, and the proportion of other elements is relatively small. Therefore, the Ca element closely related to calcite and dolomite can be used as an indicator element for lithology identification of carbonate rocks; the main oxides in igneous rocks are SiO₂ and Al₂O₃, followed by K₂O+Na₂O and Fe₂O₃, among which SiO₂ accounts for the largest proportion, so Si is the main mineral element of igneous rocks and can be used as an indicator element for lithology identification of igneous rocks.

[0027] Preferably, the identification parameter discriminant formula described in step (4) is Ca / Si. When Ca / Si≥A, the lithology is carbonate rock; when Ca / Si<A, the lithology is igneous rock;

[0028] The value of A is 1-1.5, for example, it can be 1, 1.1, 1.2, 1.3, 1.4 or 1.5, but it is not limited to the listed values, and other unlisted values within the numerical range are also applicable.

[0029] Preferably, the formula of the lithology index parameter described in step (6) is: L ig =(Th / K)×Fe; where Th is the logging value of Th element from GR spectral logging, K is the logging value of K element from GR spectral logging, and Fe is the percentage content of Fe element from ECS element capture logging.

[0030] The secondary oxides of igneous rocks are K₂O+Na₂O and Fe₂O₃, among which K₂O+Na₂O mainly reflects the basicity degree of igneous rocks. In natural gamma spectral logging, 40 the relative content accuracy of K element is higher, which can replace the change of the proportion of Na+K elements in ECS element capture logging to reflect the basicity degree; Fe element is related to minerals such as pyrite and hematite, and can also reflect the basicity degree of igneous rocks; Th in natural gamma spectral logging is correlated with the formation sedimentary environment, rock lithology and grain size; combining ECS element capture logging and natural gamma spectral logging, the Th spectral logging curve, K spectral logging curve and Fe capture logging curve can be used as indicator elements for lithology identification, so as to accurately identify extrusive rocks and intrusive rocks in igneous rocks.

[0031] Preferably, when L ig ≥B, the lithology is diabase; when L ig <B, the lithology is basalt;

[0032] The value of B is 15-25, for example, it can be 15, 16, 18, 20, 21, 24 or 25, but it is not limited to the listed values, and other unlisted values within the numerical range are also applicable.

[0033] As a preferred technical solution of the igneous rock lithology identification method according to the present invention, the igneous rock lithology identification method comprises the following steps:

[0034] (1) Standardize the logging curves of the to-be-evaluated formation of the study well to obtain standardized logging curves of the to-be-evaluated formation of the study well; the logging curves include caliper curve CAL, natural gamma logging curve GR, natural gamma spectrum logging curve, neutron logging curve NPHI, density logging curve RHOB and ECS element capture logging curve;

[0035] (2) Load the lithology of sidewall coring and thin section core depth points of the to-be-evaluated formation of the study well, select sample points with obvious logging characteristics to ensure the accuracy of lithology identification;

[0036] (3) Based on the sample points selected in step (2), determine the logging response characteristics of two major categories of lithology according to the sensitive logging curves; the sensitive logging curves include any one or a combination of at least two of density logging curve RHOB, natural gamma spectrum logging curve or ECS element capture logging curve;

[0037] (4) Use the sensitive logging curves described in step (3) to establish a neutron-density logging crossplot and a Ca-Si logging crossplot, and combine the logging response characteristics of the two major lithology categories of carbonate rock and igneous rock to establish an identification parameter discriminant formula, so as to obtain carbonate rock lithology and igneous rock lithology; the identification parameter discriminant formula is Ca / Si, when Ca / Si≥A, the lithology is carbonate rock; when Ca / Si<A, the lithology is igneous rock; the Ca is the percentage content of Ca element from ECS element capture logging, and Si is the percentage content of Si element from ECS element capture logging;

[0038] (5) For the igneous rock lithology obtained in step (4), based on the lithology of sidewall coring and thin section core depth points, combined with ECS element logging and GR spectrum logging, establish an identification chart for intrusive rock and extrusive rock;

[0039] (6) Perform igneous rock lithology identification according to the lithology index parameters of the identification chart obtained in step (5), so as to identify intrusive rock and extrusive rock; the formula of the lithology index parameter is: L ig =(Th / K)×Fe, when L ig ≥B, the lithology is diabase; when L ig <B, the lithology is basalt; Th is the Th element logging value of GR spectrum logging, K is the K element logging value of GR spectrum logging, and Fe is the percentage content of Fe element from ECS element capture logging.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] This invention provides a method for identifying igneous rock lithology based on ECS elemental logging. This method can adapt to the identification of igneous rock lithology in complex lithological areas, taking into account both carbonate rock development and various types of igneous rocks, thus improving the identification quality of igneous rocks in complex lithological areas. Furthermore, the igneous rock lithology identification method provided by this invention has high discrimination accuracy and is relatively simple, which is conducive to achieving automatic and efficient identification and has good application prospects. Attached Figure Description

[0042] Figure 1 The process flow diagram of the igneous rock lithology identification method provided in Example 1 is shown below.

[0043] Figure 2 This is a neutron-density cross plot of the two main types of lithology, igneous rocks and carbonate rocks, in Example 1;

[0044] Figure 3 This is the Ca-Si well logging cross plot from Example 1;

[0045] Figure 4 This is a lithological identification chart of igneous rocks and carbonate rocks in Example 1;

[0046] Figure 5 This is an identification chart for lithological identification of diabase and basalt in Example 1;

[0047] Figure 6 This is a diagram showing the lithological identification results of a certain igneous rock section in Well A in Example 1. Detailed Implementation

[0048] The technical solution of the present invention will be further illustrated below through specific embodiments. Those skilled in the art should understand that the embodiments described are merely illustrative of the present invention and should not be construed as limiting the invention in any way.

[0049] To clearly illustrate the technical solution of the present invention, the specific embodiments of the present invention conduct lithological identification of intrusive rocks (mainly diabase) and eruptive rocks (mainly basalt) under salt in the Santos Basin of Brazil. The layer to be evaluated in the study well is the Cretaceous strata of the Santos Basin in the Brazilian sea area.

[0050] Example 1

[0051] This embodiment provides a method such as Figure 1 The illustrated method for identifying igneous rock lithology based on ECS elemental logging includes the following steps:

[0052] (1) The logging curves of the layer to be evaluated in the study well are subjected to conventional preprocessing, quality analysis and standardization to remove the influence of wellbore enlargement, outliers and systematic deviations caused by different logging instruments, so as to obtain the standardized logging curves of the layer to be evaluated in the study well; the logging curves include the wellbore diameter curve CAL, natural gamma logging curve GR, natural gamma spectral logging curve, neutron logging curve NPHI, density logging curve RHOB and ECS element capture logging curve;

[0053] The natural gamma spectral logging curves include TH spectral logging curves, U spectral logging curves, and K spectral logging curves;

[0054] The ECS element capture logging curves include Ca capture logging curves, Si capture logging curves, Fe capture logging curves, Na capture logging curves, and K capture logging curves;

[0055] (2) Load the lithology of the wellbore core and thin section core depth points of the layer to be evaluated in the research well, perform quality analysis on all sample points, screen out sample points with unclear lithological characteristics in wellbore core and unclear lithological observation characteristics in thin section, and select sample points with no enlargement effect and obvious logging characteristics to ensure the accuracy of lithology identification.

[0056] (3) Based on the sample points selected in step (2), perform two-parameter cross-plot analysis and three-parameter cross-plot analysis to determine the sensitive logging curves, and determine the two major categories of lithological logging response characteristics based on the sensitive logging curves; the sensitive logging curves include density logging curve RHOB, natural gamma ray spectroscopy logging curve and ECS element capture logging curve;

[0057] (4) Use the sensitive logging curves described in step (3) to establish a neutron-density logging cross-plot (see Figure 2 Cross-plot with Ca-Si logging (see) Figure 3 Combining the logging response characteristics of two major lithological categories—carbonate rocks and igneous rocks—a discriminant formula for identification parameters was established, and a lithological identification chart for carbonate rocks and igneous rocks was obtained by fitting the formula (see [link]). Figure 4 The lithology of carbonate rocks and igneous rocks is obtained; the discriminant of the identification parameter is Ca / Si, derived from... Figure 4 It can be seen that when Ca / Si≥1.2, the lithology is carbonate rock; when Ca / Si<1.2, the lithology is igneous rock; Ca refers to the percentage content of Ca element in ECS element capture logging, and Si refers to the percentage content of Si element in ECS element capture logging.

[0058] Igneous rocks typically have a high density, with values ​​often exceeding 2.65 g / cm³. 3 The average value is 2.8 g / cm³. 3 The carbonate rock is homogeneous with a density of 2.46 g / cm³. 3, with an average neutron value of 13%. From Figure 2 , it can be seen that there is an obvious difference in density between carbonate rocks and igneous rocks. From Figure 3 , it can be seen that in ECS elemental capture logging, Ca and Si are sensitive to the lithology of carbonate rocks and igneous rocks with obvious distinction;

[0059] (5) For the igneous lithology obtained in step (4), based on the lithology at the depth points of sidewall core and thin-section core, combined with ECS elemental capture logging and natural gamma ray spectroscopy logging, an identification chart for intrusive rocks (dominated by diabase) and extrusive rocks (dominated by basalt) is established (see Figure 5 );

[0060] (6) Lithology identification of igneous rocks is carried out using the lithology index parameters of the identification chart obtained in step (5) (see Figure 5 ), to identify intrusive rocks and extrusive rocks; the formula of the lithology index parameter is: L ig =(Th / K)×Fe, when L ig ≥B, the lithology is intrusive rock dominated by diabase; when L ig <B, the lithology is extrusive rock dominated by basalt; Th is the logging value of Th element from GR spectroscopy logging, K is the logging value of K element from GR spectroscopy logging, and Fe is the percentage content of Fe element from ECS elemental capture logging;

[0061] Fitted based on the lithology and logging data of the study area, the value of B in this embodiment is 20.

[0062] Figure 6 is a diagram showing the igneous lithology identification results of a certain interval in Well A. The 2nd track therein is the natural gamma ray and uranium-free gamma ray track, and the igneous rock interval shows medium-high gamma; the 5th track is the sidewall core and thin section calibration track, containing three lithologies of limestone, diabase and basalt; the 6th track is Ca / Si ratio discrimination, the filled part indicates Ca / Si≥1.2, which refers to carbonate rock, and the unfilled part indicates Ca / Si<1.2, which refers to igneous rock; the 7th track is the lithology index parameter L ig , the filled part indicates L ig ≥20, which refers to diabase, and the unfilled area indicates L ig <20, which refers to basalt; the 3rd track is the lithology of cuttings logging, and the 4th track is the lithology identified by the innovative igneous lithology identification method.

[0063] Through comparison with thin section and sidewall core analysis, a total of 92 samples are counted, including 33 diabase samples, 27 of which are matched, with a coincidence rate of 81.82%; 59 basalt samples, 51 of which are matched, with a coincidence rate of 96.44%, and the comprehensive lithology coincidence rate reaches 84.78%, which proves that the igneous lithology identification result in this embodiment is reliable.

[0064] In summary, this invention provides a method for identifying igneous rock lithology based on ECS elemental logging. This method is adaptable to igneous rock lithology identification in complex lithological zones, taking into account both carbonate rock development and various types of igneous rocks, thus improving the identification quality of igneous rocks in complex lithological zones. Furthermore, the igneous rock lithology identification method provided by this invention has high discrimination accuracy and is relatively simple, which is conducive to achieving automatic and efficient identification and has good application prospects.

[0065] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Those skilled in the art should understand that any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention fall within the scope of protection and disclosure of the present invention.

Claims

1. A method for identifying igneous rock lithology based on ECS elemental logging, characterized in that, The igneous rock lithology identification method comprises the following steps: (1) Performing standardization processing on the logging curves of the layer to be evaluated in the study well to obtain standardized logging curves of the layer to be evaluated in the study well; the logging curves include caliper logging curve CAL, natural gamma logging curve GR, natural gamma spectrum logging curve, neutron logging curve NPHI, density logging curve RHOB and ECS element capture logging curve; (2) Obtaining the lithology at the sidewall coring and thin section core depth points of the layer to be evaluated in the study well, selecting sample points with obvious logging characteristics to ensure the accuracy of lithology identification; (3) Based on the sample points selected in step (2), determining two major categories of lithology logging response characteristics according to the sensitive logging curves; The sensitive logging curves include any one or a combination of at least two of density logging curve RHOB, natural gamma spectrum logging curve or ECS element capture logging curve; (4) Using the sensitive logging curves described in step (3) to establish a neutron-density logging crossplot and a Ca-Si logging crossplot, and combining the lithology logging response characteristics of the two major categories of carbonate rock and igneous rock to establish an identification parameter discriminant formula, so as to obtain carbonate rock lithology and igneous rock lithology; the identification parameter discriminant formula is Ca / Si, when Ca / Si≥A, the lithology is carbonate rock; when Ca / Si<A, the lithology is igneous rock; the Ca is the percentage content of Ca element from ECS element capture logging, and Si is the percentage content of Si element from ECS element capture logging; (5) For the igneous rock lithology obtained in step (4), based on the lithology at the sidewall coring and thin section core depth points, combined with ECS element capture logging and natural gamma spectrum logging, an intrusive rock and extrusive rock identification chart is established; (6) Performing igneous rock lithology identification according to the lithology index parameter of the identification chart obtained in step (5), to identify intrusive rocks and extrusive rocks; the formula of said lithology index parameter is: L ig =(Th / K)×Fe, when L ig ≥B, the lithology is diabase; when L ig <B, the lithology is basalt; Th is the logging value of Th element from GR spectrum logging, K is the logging value of K element from GR spectrum logging, and Fe is the percentage content of Fe element from ECS element capture logging.

2. The method for identifying igneous rock lithology according to claim 1, characterized in that, The natural gamma spectrum logging curve includes any one or a combination of at least two of TH spectrum logging curve, U spectrum logging curve or K spectrum logging curve.

3. The method for identifying igneous rock lithology according to claim 1, characterized in that, The ECS element capture logging curve includes any one or a combination of at least two of Ca capture logging curve, Si capture logging curve, Fe capture logging curve, Na capture logging curve or K capture logging curve.

4. The method for identifying igneous rock lithology according to claim 1, characterized in that, The value of A described in step (4) is 1-1.

5.

5. The method for identifying igneous rock lithology according to claim 1, characterized in that, The value of B is 15-25.

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