CN114137633B - Volcanic rock facies step-by-step identification method - Google Patents
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Abstract
The invention provides a volcanic rock facies progressive identification method, which comprises the following steps: acquiring drilled data, logging data, magnetic anomaly data and seismic data, and dividing known volcanic rock facies types; establishing a phase-magnetic relationship plate, a phase-electric relationship plate and a phase-vibration relationship plate; according to the magnetic anomaly condition in the phase-magnetic relationship plate, primarily dividing a lithofacies range on the magnetic anomaly data; according to the key parameter inversion in the phase-electric relation plate, further subdividing lithofacies on the logging data; and carrying out seismic section reflection characteristic analysis on the seismic data according to the phase-seismic relation plate to finish the step-by-step identification of the volcanic rock facies. The method provided by the invention adopts 'well-magnetic-electric-vibration' step-by-step control to predict the volcanic rock facies, reduces the polycompositivity brought by single method for predicting the rock facies, and can more accurately predict the distribution of the volcanic rock facies.
Description
Technical Field
The invention relates to the technical field of volcanic reservoir rock phase identification in the petroleum industry, in particular to a volcanic rock phase step-by-step identification method.
Background
Along with the continuous discovery of volcanic oil and gas reservoirs at home and abroad, the volcanic oil and gas reservoir is a special oil and gas reservoir and is widely valued by petroleum companies at home and abroad. Exploration practices and related researches prove that in volcanic oil and gas reservoir evaluation, a favorable reservoir is a key for successful volcanic oil and gas reservoir exploration, and lithofacies identification is one of main contents of volcanic reservoir research. Due to the later-stage strong ablation and transformation, volcanic mechanism is incomplete, volcanic rock facies are discontinuous on a plane, the lithofacies and lithology are greatly changed, the heterogeneity is strong, oil gas is often accumulated in volcanic breccia or volcanic lava with developed pore cracks, and lithology identification is a key and difficult point of volcanic oil reservoir evaluation.
At present, foreign research on the lithofacies identification of volcanic rocks is more important to the microseism technology and the horizon interpretation of seismic data, and China is more important to the development of the volcanic rock facies earthquake prediction technology. Compared with the identification of igneous rock facies, the identification of volcanic rock facies has the problems that the volcanic rock facies change rapidly and the physical properties are complex, and the specific lithofacies such as volcanic lava, volcanic clastic rock and the like in volcanic rock are difficult to be identified by directly utilizing seismic data. The volcanic hydrocarbon reservoir has high drilling cost and high risk, so that accurate identification of volcanic lithofacies is very important. In the case of the existing volcanic rock facies identification method, the single method has multiple solutions, and a good prediction effect is difficult to obtain.
Disclosure of Invention
In order to solve the problems, the invention aims to provide a volcanic rock facies progressive identification method. The identification method adopts a method of predicting volcanic rock facies by step-by-step control of 'well-magnetic-electric-vibration', reduces the polycrystallinity brought by single method for predicting the rock facies, and can more accurately predict the distribution of the volcanic rock facies.
In order to achieve the above object, the present invention provides a method for stepwise identifying volcanic rock facies, comprising:
step one, acquiring drilled data, logging data, magnetic anomaly data and seismic data, and dividing known volcanic lithofacies types;
step two, establishing a phase-magnetic relationship drawing board, a phase-electric relationship drawing board and a phase-vibration relationship drawing board;
step three, primarily dividing the lithology range of the magnetic anomaly data according to the magnetic anomaly condition in the phase-magnetic relationship plate;
step four, based on the division result of the step three, further dividing lithofacies of the logging data according to key parameter inversion in the phase-electric relation plate;
and fifthly, carrying out seismic section reflection characteristic analysis on the seismic data according to the phase-seismic relation plate, and comprehensively explaining by utilizing the division results of the third step and the fourth step to finish the step-by-step identification of the volcanic lithofacies.
The volcanic rock facies progressive identification method can fully play the advantages of various data and make up the respective defects; meanwhile, by combining drilling data and logging interpretation, the interpretation result is more objective, and the reliability of interpretation is improved. According to the identification method, through deep excavation of the rock core, logging and other data of a research area, the lithology and lithology of the drilled volcanic rock can be subdivided, a phase-electric relation chart, a phase-magnetic relation chart and a phase-earthquake relation chart are established by combining the logging curve, the magnetic anomaly and the earthquake data, response characteristics of the lithology and lithology in the magnetic anomaly, the electric property and the earthquake relation are fully utilized, targeted inversion is carried out according to a typical curve capable of distinguishing the lithology and lithology, and the thinking of mutual evidence, step-by-step prediction and step-by-step elimination of multiple methods is adopted, so that the accuracy of prediction is improved.
In accordance with an embodiment of the present invention, in step one, the facies classification process may include using the well logging data and coring data from the well to classify the facies uphole and determine the volcanic facies type. In some embodiments, the method of determining the volcanic rock facies type in step one may specifically include: the rock phase type is judged by utilizing the drilled rock core and determining the characteristic lithology, characteristic structure and the like of the rock sample through rock core observation, microscopic slice identification and the like. For example: and judging that the rock samples with lithology of curdling sand and the like, characteristic structures of land source detritus structures, characteristic structures of block structures, rhythm layer structures, horizontal layer structures, staggered layer structures, groove layer structures and grain sequence layer structures belong to volcanic sediment phases.
In accordance with an embodiment of the present invention, in step one, the magnetic anomaly data generally comprises a magnetic anomaly plan view; the magnetic anomaly plan is generally a high-precision magnetic anomaly plan, the precision of the magnetic anomaly plan can be controlled to be 1:5 ten thousand, and the total error is generally not more than 5nT.
In accordance with an embodiment of the present invention, in step one, the well log data may include a resistivity log and a natural gamma log.
In accordance with an embodiment of the present invention, in step one, the seismic data generally includes a seismic phase waveform classification attribute map.
According to a specific embodiment of the present invention, in the second step, the phase-magnetic relationship plate, the phase-electric relationship plate and the phase-vibration relationship plate may be established by a method of intersection graph analysis. The intersection graph generally displays data points in a two-dimensional coordinate system in the form of scattered points, and can comprehensively analyze information represented by the data by observing and analyzing the distribution form of the data and the relation among various data.
According to a specific embodiment of the invention, in the second step, a phase-magnetic relationship plate can be established by combining response characteristics of different lithofacies which have been drilled on the magnetic anomalies.
According to a specific embodiment of the present invention, the method for acquiring magnetic anomalies generally comprises: and performing magnetic anomaly extension calculation on the magnetic anomaly data to obtain residual magnetic anomalies of the base of the research area, and extracting the magnetic anomalies caused by volcanic rock through extension, filtering and forward delamination. Starting from the drilled lithofacies and the magnetic anomaly data, counting the magnetic anomaly data of different lithofacies, making a scattered point cross-plot, analyzing the magnetic anomaly range characteristics of different lithofacies, and establishing a magnetic anomaly information plate of different lithofacies.
According to a specific embodiment of the invention, in the second step, a phase-electric relationship plate can be established by combining the electric response characteristics of different lithofacies which are drilled in a logging curve.
According to an embodiment of the present invention, the method for acquiring a log generally includes: by measuring the electrochemical characteristics, conductive characteristics, radioactivity and other geophysical characteristics of the rock stratum, a logging curve is obtained, and when the geophysical information is measured, a surface electric measuring instrument can be put into the well through a logging cable, so that the surface electric measuring instrument can continuously record various parameters which change along with the depth of a well shaft.
In the specific embodiment of the invention, the lithology and lithofacies of volcanic rock of the whole well section of the well drilling can be well identified by using the change characteristics of the logging curve. And (3) according to typical logging curve response characteristics of different lithofacies statistical samples, making a logging curve data scattered point intersection graph, dividing logging curve data response ranges of different lithofacies, and establishing a phase-electric relation graph plate.
According to a specific embodiment of the invention, in the second step, a facies-seismic relationship plate can be established by combining response characteristics of different lithofacies which have been drilled on the seismic section.
According to an embodiment of the present invention, the method for acquiring a seismic section generally includes: and (3) acquiring and processing data to form a section of the impedance reflection interface of the underground wave, and summarizing the seismic reflection characteristics of the volcanic lithology from the seismic response characteristics corresponding to the volcanic lithology and lithology combination of the known well to establish a lithology and seismic relation plate. In some embodiments, the reflection characteristics of the seismic profile are primarily characterized by differences in morphology, continuity, amplitude, frequency, etc. If the burst phase mainly takes volcanic breccia as main material, the appearance is shield-shaped or residual shield-shaped, the interior is disordered or blank reflection, medium-low frequency, medium amplitude and poor continuity.
In the specific embodiment of the invention, the volcanic rock facies progressive identification method adopts objective seismic attribute and cluster analysis seismic facies technology, realizes the identification of the basement lithology on a plane, improves the accuracy of lithology identification, and has important reference significance for the basement lithology identification of the basin (especially the eastern basin of China).
According to an embodiment of the present invention, step three includes classifying the pozzolan phase and the volcanic overflow phase, the sedimentary phase, and the volcanic sedimentary phase on the magnetic anomaly data based on the magnetic anomaly response characteristics. In a specific embodiment of the present invention, preferably, the magnetic anomaly data of the volcanic eruption phase and the volcanic overflow phase are strong positive anomalies, the magnetic anomaly data of the volcanic sedimentary phase are weak magnetic anomalies, and the magnetic field data of the sedimentary phase are negative magnetic anomalies. In some embodiments, the pozzolanic and volcanic overflow phases generally have magnetic anomaly data between (+150 nT) and (+1000 nT), the volcanic sedimentary phases generally have magnetic anomaly data between (-150 nT) and (+150 nT), and the sedimentary phases generally have magnetic anomaly data between (-600 nT) and (-150 nT).
In step four, the key parameters are typically key parameters of the log, such as the resistance value (RT value) and the natural gamma value (GR value), etc.
According to a specific embodiment of the present invention, in step four, the method of further subdividing lithofacies on the logging data may include: and dividing the region with the resistance value of more than or equal to 35-45 omega m in the logging data into a volcanic overflow phase and a sedimentary phase by taking the phase-electric relation plate as a dividing basis, and dividing the region with the resistance value of less than 35-45 omega m into a volcanic clastic phase (including volcanic eruption rock phase) and a volcanic sedimentary phase. And step four, the volcanic overflow phase is divided by utilizing a natural gamma value, the area with the natural gamma value smaller than 70-80API in the logging data is divided into basic volcanic overflow phases (such as basalt), and the area with the GR value larger than or equal to 70-80API is divided into medium-acid volcanic overflow phases (such as andesite and flow rock).
In accordance with a specific embodiment of the present invention, in step five, the seismic profile reflection characteristic data phase attribute analysis generally comprises: describing the spatial variation of geological information, and dividing and classifying seismic phases according to the variation of seismic waveforms; and calibrating geological information according to the seismic phase distribution, so as to obtain a lithogram corresponding to the seismic phase distribution, and completing the step-by-step identification of the volcanic lithology. In some embodiments, the seismic phase properties may include, in particular, profile, internal features, continuity, amplitude, frequency, phase, and the like.
According to a specific embodiment of the present invention, in the fifth step, the specific process of analyzing the seismic profile reflection characteristic data phase attribute may be: describing the spatial variation of the geological information by extracting the spatial similarity of the seismic information; in a time window of a specific target layer, according to the waveform characteristics of the seismic channels, describing the transverse change of the seismic waveforms, and distinguishing different seismic phase types on a plane; according to the waveform classification result, each seismic channel forms discrete seismic phases, and plane classification is carried out on the discrete seismic phases to obtain a plane seismic phase diagram; and then calibrating the geological information revealed by the drilled well, comprehensively geologically explaining the waveform classification result, and finally obtaining a lithogram corresponding to the seismic facies distribution, namely converting the seismic facies into lithofacies, thus finishing the step-by-step identification of the volcanic lithofacies.
The beneficial effects of the invention include:
1. the identification method combines geological-seismic data, adopts the thought of gradually controlling and identifying volcanic rock facies by 'well-magnetic-electric-vibration', forms a set of new technology for gradually identifying the volcanic rock facies, reduces the multiple solutions of the volcanic rock facies identification, can accurately predict the spreading range of various rock facies on a plane, and provides technical support for searching volcanic rock facies favorable areas in oil fields;
2. from the actual drilling result, various lithofacies development areas identified by the volcanic rock facies progressive identification technology have good coincidence relation with the drilling result. Exploration practices prove that the thought and the technique are feasible for predicting the volcanic rock facies, and are worthy of popularization and application in similar areas.
Drawings
FIG. 1 is a phase-magnetic relationship plate of example 1.
FIG. 2 is a phase-electrical relationship chart of example 1.
FIG. 3 is a plot of the phase-shock relationship of example 1. Wherein, a diagram is a volcanic eruption phase seismic response diagram; b is a plot of the seismic response of the volcanic overflow phase; and c is a seismic response diagram of the volcanic sedimentary phase.
Fig. 4 is a magnetic anomaly partition lithogram of example 1.
FIG. 5 is an inversion plot of the resistivity log of example 1.
FIG. 6 is an inversion plot of the natural gamma log of example 1.
Fig. 7 is a seismic-phase waveform classification attribute plan view of embodiment 1.
Fig. 8 is a volcanic rock phase identification plan view of example 1.
Fig. 9 is a lithology graph of the actual drilling of the study area of example 1.
Detailed Description
The technical solution of the present invention will be described in detail below for a clearer understanding of technical features, objects and advantageous effects of the present invention, but should not be construed as limiting the scope of the present invention.
Example 1
The embodiment provides a method for gradually identifying volcanic rock facies, wherein a research area of the method is a Madong slope area of a Pascal basin, the volcanic rock facies of the area are complex and change quickly, and multiple solutions exist by using the existing single identification technology.
The acquisition methods of the reflection characteristic data of the magnetic anomaly, the logging curve and the seismic section in the embodiment are respectively as follows:
the method for acquiring the magnetic anomaly data comprises the following steps: firstly, obtaining a surrounding geological magnetic field by using a filtering method, and reducing a regional magnetic field from the weak pole abnormality of the magnetic force to obtain residual magnetic abnormality information so as to realize the aim of suppressing the influence of an underground deep magnetic surface body; on the basis of comparative analysis of a series of known research results, magnetic field depth separation is utilized to carry out key extraction on magnetic force abnormality information respectively, relevant analysis signals are obtained, and specific magnetic force abnormality information reflecting a target mining area is finally obtained. Through a series of processes of upward extension and downward extension of weakened magnetic force abnormality information, abnormality of a residual magnetic field is obtained, and the abnormality is compared by means of actual detection data, so that the magnetic abnormality characteristics caused by the depth magnetic meter body at different depths are known.
The logging curve data acquisition method comprises the following steps: the method comprises the steps of utilizing the electrochemical characteristics, conductive characteristics, radioactivity and other geophysical characteristics of the rock stratum, obtaining the characteristics by measuring geophysical parameters, and lowering a ground electric measuring instrument into a well through a logging cable, so that the ground electric measuring instrument can continuously record various parameters which change along with the depth along a well shaft. The obtained main geophysical parameters include natural gamma value (GR), resistance value (RT), density value (DEN), acoustic time difference value (AC) and the like.
The method for acquiring the reflection characteristic data of the seismic section comprises the following steps: by collecting and processing data, a section of a subsurface wave impedance reflection interface is formed, and the reflection characteristics of the seismic section are mainly represented by different parameters such as morphology, continuity, amplitude, frequency and the like.
Specifically, the volcanic rock facies progressive identification method provided by the implementation comprises the following steps:
1. and collecting the data of the drilled rock core in the working area, performing rock core observation, sheet identification under a lens and the like, determining the characteristic lithology of the rock sample by observing the color, structure, silicon dioxide content, mineral composition and content thereof and the like of the rock core, and obtaining a high-precision magnetic anomaly plan of the target area. In this example, the characteristic lithology included in the rock sample was observed to be several of the following:
basalt: dark color, a spot structure, a grain structure, a block structure, an almond structure, a small amount of air holes structure, and the silicon dioxide content is 45-52%.
Andesite rock: neutral volcanic lava, common zebra structure, zebra micro-interweaved structure and disintegrated interweaved structure, almond structure, air hole structure, and silicon dioxide content of 52-63%.
The flow vein rock: the color is off-white or light pink, and the glass structure, the spherical structure, the fine structure and the microscopic structure are commonly provided with flow marks and speckled structures, and the silicon dioxide content is more than 68 percent.
Volcanic breccia: has a volcanic gravel structure and a block structure, the rock debris is more than 2mm, and the content of the gravel component is greatly changed.
Tuff stone: the color is various, the boulder crystal scraps and rock scraps are in a condensed ash structure and a block structure, and the rock consists of crystal scraps, rock scraps, boulders and cementing agent volcanic ash. The lumpy or lamellar volcaniclastic rock is composed of volcaniclastic material with particle diameter of less than 2mm and 50% or more, and mainly contains volcaniclastic ash.
Setting limestone: is a rock type which transits from normal volcaniclastic rock to normal sedimentary rock, the volcaniclastic content is 75-25%, and the normal sedimentary rock is the less than 25%. A setting ash structure and a block structure.
Tuff sandstone: the crumb particle size is 0.1-2mm, and is predominantly normal sedimentary, containing a certain amount (< 50%) of the type of rock. And (3) a greywater structure and a banza structure.
Sandstone: the main component of sedimentary rock is clay mineral, and contains a small amount of sand. The layering is not obvious, or the layers are in a block shape.
Identifying basalt, andesite and streak rock belonging to volcanic overflow phases; volcanic breccia and tuff belonging to volcanic burst phase; tuff, tuff and sandstone belonging to the volcanic sediment phase; and sandstone belonging to the sedimentary phase.
2. Combining response characteristics of different lithofacies of known well drilling in magnetic anomaly, logging curve and seismic section respectively, respectively establishing a phase-magnetic relationship chart, a phase-electric relationship chart and a phase-seismic relationship chart, wherein the specific modes are as follows:
1) According to the magnetic anomaly data corresponding to the drilled rock phase, a phase-magnetic relationship chart is established as shown in fig. 1:
through statistics of magnetic susceptibility data of different lithology lithofacies of the drilled well, data points are displayed in a two-dimensional coordinate system in the form of scattered points, the abscissa is the number of samples (a plurality of samples), the ordinate is the magnetic anomaly (nT), and a phase-magnetic relation plate is established. By observing and analyzing the distribution form of the data, the distribution range of the magnetic anomaly data of the volcanic eruption phase and the volcanic overflow phase is between (+ 150 nT) and (+ 1000 nT), and the magnetic anomaly data is strong positive anomaly; the volcanic sediment phase magnetic anomaly data are distributed between (-150 nT) and (+ 150 nT) and are weak magnetic anomalies; the distribution range of the deposition phase magnetic anomaly data is between (-600 nT) and (-150 nT), and the deposition phase magnetic anomaly data is negative magnetic anomaly.
2) According to the electrical response characteristics of the logging curves corresponding to the drilled lithofacies, selecting characteristic curves capable of distinguishing various lithofacies, and establishing a facies-electrical relationship plate shown in fig. 2:
in this embodiment, the characteristics of the sensitivity curves GR (natural gamma value), DEN (density value), RT (resistance value), and AC (acoustic time difference value) of the typical well corresponding to the lithology of the sample are selected, so as to more intuitively and obviously represent the characteristics of the logging curves of various lithologies, and the specific logging response characteristics of the lithologies are as follows:
basalt: medium-high resistance (30-118. OMEGA.m), low gamma (33-73 API), medium-high density (2.68-2.84 g/cm) 3 ) Low acoustic wave time difference (55-61 API).
Andesite rock: middle resistance (39-94. OMEGA.m), middle gamma (71-133 API), middle density (2.50-2.83 g/cm) 3 ) Low acoustic wave time difference (50-57 API).
The flow vein rock: medium resistance (32-76. OMEGA.m), high gamma (86-107 API), low density (2.25-2.45 g/cm) 3 ) Low acoustic wave time difference (61-70 API).
Volcanic breccia: low-medium resistance (3-42. OMEGA.m), medium gamma (57-103 API), low density (2.34-2.62 g/cm) 3 ) High acoustic time difference (57-85 API).
Tuff stone: low-medium resistance (3-32 Omegam), high gamma (80-117 API), low density (2.34-2.62 g/cm) 3 ) High acoustic time difference (55-86 API).
Setting limestone: low resistance (3-10Ω m), low gamma (31-47 API), low density (2.20-2.35 g/cm) 3 ) High acoustic time difference (91-110 API).
Tuff sandstone: low resistance (4-10Ω m), low gamma (45-54 API), low density (2.20-2.43 g/cm) 3 ) High acoustic time difference (90-117 API).
Sandstone: low-medium resistance (30-69. OMEGA.m), low gamma (37-46 API) low-medium density (2.49-2.57 g/cm) 3 ) Medium acoustic time difference (66-72 API).
In this embodiment, the samples of the fire breccia and tuff are low in purity, the tuff is mixed in the volcanic breccia, and the tuff is mixed in the tuff sample, so that the resistance value and the natural gamma value of the two samples are relatively close. In the sample with higher purity, the resistance value of the volcanic breccia is higher than that of the tuff, and the natural gamma value of the volcanic breccia is lower than that of the tuff.
And (3) through statistics of the electrical response characteristic data of the lithofacies logging curve, displaying data points in a two-dimensional coordinate system in a scattered point form, and establishing a facies-electrical relation plate.
As can be seen from the graph of the phase-electrical relationship in FIG. 2, the volcanic overflow phase has a high resistance value, typically greater than 35-45. OMEGA.m, and other phases have lower resistance values. From basalt-andesite-meteoroid, the natural gamma value is from low to high. Thus, from fig. 2, the basic overflow phase volcanic rock (basalt), neutral overflow phase volcanic rock (andesite) and acid overflow phase volcanic rock (striae) can be distinguished, and the volcanic overflow phase and volcanic burst phase can be distinguished obviously.
3) According to different response characteristics of different lithofacies on earthquakes, a phase-earthquake relation graph plate shown in fig. 3 is established, wherein a graph a of fig. 3 is an earthquake response graph of volcanic eruption phase, b of fig. 3 is an earthquake response graph of volcanic overflow phase, c of fig. is an earthquake response graph of volcanic sedimentary phase, the areas surrounded by white boundaries in the graphs are earthquake phases identified according to the earthquake response characteristics, and the earthquake response graph of the sedimentary phase is similar to the earthquake response graph of the volcanic sedimentary phase:
and (3) starting from the seismic reflection characteristics corresponding to the volcanic lithology and lithology combination of the known well, selecting a typical lithology lithofacies well, and analyzing the seismic reflection interface, the form, the amplitude, the frequency, the internal and external characteristics and the like of the well. For example: the drilled wells, which are predominantly volcanic breccia, exhibit weak amplitude clutter discontinuous reflections on seismic sections, approaching the crater. The overflow phase is the dominant well drilled, with mid-weak amplitude more continuous parallel reflections on the seismic profile. The well bore, which is dominated by the volcanic sedimentary phase, exhibits strong amplitude continuous parallel reflections on the seismic profile. And then, counting reflection characteristics of different lithofacies in the seismic section, displaying data points in a two-dimensional coordinate system in a scattered point form, and establishing a facies-seismic relation plate.
The reflection characteristics of different lithofacies in a seismic section are as follows:
the volcanic overflow phase mainly comprises basalt, andesite and meteoroid, and has wedge-shaped, hilly, mat-shaped and lenticular appearance, and the internal reflection is characterized by inclined lamellar reflection, good continuity, strong-medium amplitude, medium-low frequency reflection and parallel-subparallel reflection structure.
The volcanic eruption phase mainly comprises volcanic breccia and tuff, the top of the volcanic eruption phase is provided with arc-shaped features, the appearance is shield-shaped or residual shield-shaped, the internal structure is disorder or blank reflection features, weak reflection, medium and low frequency, medium amplitude and poor continuity.
The volcanic sediment phase is mainly tuff, tuff sand, tuff sandstone and tuff mudstone, and has a layered or hilly appearance, a medium-weak amplitude and weak reflection inside, a parallel-subparallel inside, a large inclination angle emission and good-medium continuity.
Deposition phase: sandstone is the main material, and weak-middle reflection, mat-shaped appearance and sub-parallel are continuous.
3. And (4) primarily dividing the explosion phase, overflow phase, volcanic sedimentary lithofacies and sedimentary lithofacies on the high-precision magnetic anomaly plan by taking the phase-magnetic relationship plate shown in fig. 1 as a division basis, so as to obtain the magnetic anomaly division lithofacies diagram shown in fig. 4.
The specific dividing method comprises the following steps: the strong positive magnetic anomaly corresponds to a volcanic eruption phase and a volcanic overflow phase, the negative magnetic anomaly corresponds to a sedimentary phase, and the weak magnetic anomaly between the two corresponds to the volcanic sedimentary phase.
4. And (3) taking the phase-electric relation chart plate shown in fig. 2 as a division basis, inverting the logging graph according to the resistance value on the basis of the lithofacies boundary divided in fig. 4, and further dividing the volcanic burst phase and volcanic overflow phase ranges to obtain the inversion dividing lithofacies chart of the resistance value logging graph shown in fig. 5. The specific dividing method comprises the following steps: the areas with the resistance value higher than or equal to the threshold value (35-45 omega m) are volcanic overflow phases and sedimentary phases, and the areas with the resistance value lower than the threshold value (35-45 omega m) are volcanic burst phases and volcanic sedimentary phases.
And then inverting the natural gamma value logging graph according to the natural gamma value, and dividing the range of the overflow phase basalt to obtain the inversion dividing lithogram of the natural gamma value logging graph shown in fig. 6. The specific dividing method comprises the following steps: the natural gamma value is higher than or equal to a threshold value (70-80 API) and is volcanic overflow phase andesite, volcanic overflow phase flow vein rock and volcanic burst phase tuff; the region where the natural gamma value is below the threshold (70-80 API) is volcanic overflow phase basalt. And then distinguishing volcanic overflow phase crazing rock from volcanic overflow phase crazing rock according to the fact that the integral natural gamma value of the volcanic overflow phase crazing rock is larger than that of the volcanic overflow phase crazing rock.
5. Based on the phase-seismic relation plate shown in fig. 3 and the seismic response characteristics of the known well lithology, the specific distribution range of various lithofacies is divided on the plane diagram of the seismic phase waveform classification attribute diagram by using an analogy elimination method to obtain the seismic phase waveform classification attribute plane diagram shown in fig. 7.
The specific method for acquiring the seismic phase waveform classification attribute plan view comprises the following steps: spatial variations in geologic information are described by extracting spatial similarities of the seismic information. In a time window of a 60ms mesh layer with the downward top surface of the carbocoal system, according to the waveform characteristics of the seismic channels, the trace-by-trace comparison is carried out, the dissimilarity is obtained, the similarity of each seismic channel is highlighted, the change of the seismic waveform in the transverse direction is described, finally different seismic phase types are represented by different colors on a plane, the seismic phase reflects the rock phase change, and therefore the distribution rule of the rock phase on the plane is known. Different waveform classifications (colors) represent different seismic waveform features, the same classification (color) represents the same (or similar) seismic waveform features, and a seismic phase waveform classification attribute plan is obtained. Through the calibration of the drilled well, volcanic overflow phase basalt, volcanic overflow phase andesite, volcanic burst phase tuff, sedimentary phase (mainly sandstone) and the like are identified together in fig. 7. Identifying the volcanic overflow phase region by removing andesite and basalt region; volcanic breccia is identified by excluding tuff areas in the volcanic eruption phase areas.
By integrating the above methods, the lithology of fig. 4-7 is comprehensively explained by using the drilled revisions, and finally the volcanic rock facies identification plan of the research area shown in fig. 8 is obtained, so that the step-by-step identification of the volcanic rock facies of the research area is completed.
Fig. 9 is a lithology graph of the actual drilling of the area of interest. As can be seen from fig. 8 and 9, the method for stepwise identifying volcanic rock facies provided in this embodiment has a good coincidence relation between various rock facies ranges and drilling results. The exploration practice proves that the method for gradually identifying the volcanic rock facies is practical and feasible, and is worthy of popularization and application in similar areas of volcanic rock development (such as volcanic rock development areas and the like).
Claims (10)
1. A volcanic rock facies step-by-step identification method comprises the following steps:
step one, acquiring drilled data, logging data, magnetic anomaly data and seismic data, and dividing known volcanic lithofacies types; the volcanic rock facies type comprises volcanic burst phase, volcanic overflow phase, volcanic sediment phase and sediment phase;
step two, establishing a phase-magnetic relationship drawing board, a phase-electric relationship drawing board and a phase-vibration relationship drawing board;
step three, primarily dividing the lithofacies range of the magnetic anomaly data according to the magnetic anomaly condition in the phase-magnetic relationship plate, and dividing volcanic eruption phases, volcanic overflow phases, sedimentary phases and volcanic sedimentary phases on the magnetic anomaly data according to the magnetic anomaly response characteristics; the magnetic anomaly data of the volcanic eruption phase and the volcanic overflow phase are strong positive anomalies, the magnetic anomaly data of the volcanic sedimentary phase are weak magnetic anomalies, and the magnetic field data of the sedimentary phase are negative magnetic anomalies; the magnetic anomaly data of the volcanic eruption phase and the volcanic overflow phase are between +150nT and +1000nT, the magnetic anomaly data of the volcanic sedimentation phase are between-150 nT and +150nT, and the magnetic anomaly data of the sedimentation phase are between-600 nT and-150 nT;
step four, on the basis of the division result of the step three, according to the inversion of key parameters in the phase-electric relation plate, further dividing the lithology of the logging data, wherein the key parameters comprise a resistance value and a natural gamma value, and the method for further dividing the lithology of the logging data comprises the following steps: dividing the area with the resistance value larger than or equal to 45 omega m in the logging data into volcanic overflow phases and deposition phases by taking the phase-electric relation plate as a dividing basis, and dividing the area with the resistance value smaller than 45 omega m into volcanic burst phases and volcanic deposition phases;
for the volcanic overflow phase, dividing the region with the natural gamma value of less than 80API in the logging data into basic volcanic overflow phases, and dividing the region with the natural gamma value of more than or equal to 80API into medium-acid volcanic overflow phases;
and fifthly, carrying out seismic section reflection characteristic analysis on the seismic data according to the phase-seismic relation plate, and comprehensively explaining by utilizing the division results of the third step and the fourth step to finish the step-by-step identification of the volcanic lithofacies.
2. The identification method of claim 1, wherein in step one, the classification of the facies type includes using the well log data and the coring data to classify the facies uphole and determine the volcanic facies type.
3. The identification method according to claim 1 or 2, wherein in the first step, the magnetic anomaly data includes a magnetic anomaly plan view.
4. The identification method according to claim 3, wherein in the first step, the precision of the magnetic anomaly plan is 1:5 ten thousand, and the total error is not more than 5nT.
5. The identification method according to claim 1, wherein in the second step, the phase-magnetic relationship plate, the phase-electric relationship plate and the phase-vibration relationship plate are established by a junction graph analysis method.
6. The method of claim 1 or 5, wherein in step two, a phase-magnetic relationship plate is created by combining the response characteristics of the different lithofacies drilled in the magnetic anomaly.
7. The method of claim 1 or 5, wherein in step two, a facies-electrical relationship plate is created by combining the electrical response characteristics of the different lithofacies drilled in the log.
8. The method of claim 1 or 5, wherein in step two, a facies-seismic relationship map is created by combining response characteristics of different lithofacies drilled on the seismic profile.
9. The identification method according to claim 1, wherein in the fifth step, the seismic profile reflection characteristic data phase attribute analysis includes: describing the spatial variation of geological information, and dividing and classifying seismic phases according to the variation of seismic waveforms; calibrating geological information according to the seismic phase distribution, so as to obtain a lithogram corresponding to the seismic phase distribution, and completing the step-by-step identification of volcanic lithograms;
the seismic profile reflection characteristic data includes waveform classification attributes.
10. The identification method of claim 9, wherein the waveform classification attribute comprises one or a combination of two or more of an outline, an internal feature, a continuity, an amplitude, a frequency, a phase of the seismic wave.
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