A qualitative identification method for thin mudstone interlayer in volcanic rock

Abstract

The application discloses a qualitative identification method for thin-layer mudstone interlayer in volcanic rock, which comprises the following steps: firstly, determining a mudstone section stably existing in the whole area through core observation and logging data, and taking the mudstone section as a standard section; secondly, selecting three curves (a neutron logging curve, an acoustic time difference logging curve and a density logging curve) responding best to the mudstone, standardizing logging curves of the standard section and the volcanic rock section in the whole area, and determining the peak value and the distribution range of the logging curves; selecting sample points with the best effect in the mudstone section and the volcanic rock section, taking the acoustic time difference logging curve as the horizontal coordinate, and taking the neutron logging curve and the density logging curve as the vertical coordinate respectively to establish a logging interpretation chart, qualitatively determining the identification standard of the mudstone and the igneous rock, and predicting the mudstone interlayer in the volcanic rock in a single well according to the chart. The application solves the problem of qualitative identification of the thin-layer mudstone interlayer in the volcanic rock, and provides reliable technical support for the analysis of the remaining oil potential of the igneous rock.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas extraction, and in particular to a method for qualitative identification of thin mudstone interlayers within volcanic rocks based on well logging data. Background Technology

[0002] Previous studies on volcanic rocks have primarily focused on major seismic events, neglecting the influence of thin interlayers within the volcanic rock, thus limiting identification methods. Volcanic oil and gas reservoirs vary greatly in size and exhibit strong heterogeneity. As development of volcanic oil reservoirs deepens, it has become clear that the distribution of interlayers significantly impacts remaining oil production. The lack of understanding of the distribution patterns of these interlayers leads to significant difficulties in tapping the remaining oil potential of volcanic oil and gas reservoirs, resulting in low extraction efficiency. Therefore, to scientifically develop volcanic oil and gas reservoirs, it is essential to accurately identify interlayers within the volcanic rock, study their distribution patterns, and clarify their control over remaining oil production. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a qualitative identification method for thin mudstone interlayers inside volcanic rocks, so as to identify thin mudstone interlayers inside igneous rocks, study their distribution patterns, and clarify the control of interlayers on residual oil.

[0004] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a method for qualitative identification of thin mudstone interlayers inside volcanic rocks, comprising the following steps:

[0005] (1) Selecting the standard layer as the standard logging curve: Based on the core data and logging data, select the mudstone section that is stable throughout the area above the igneous rock section as the standard layer;

[0006] (2) Standardize the logging curves of the standard layer: Statistical analysis is performed on the three logging curves of the standard layer: neutron logging curve, sonic transit time logging curve and density logging curve. The peak value and distribution range of the three logging curves are determined, and the three logging curves of the standard layer are corrected to the same peak value and distribution range.

[0007] (3) Standardize the logging curves of the volcanic rock section: Following the method in step (2), correct the three logging curves of the volcanic rock section to the same peak value and distribution range;

[0008] (4) Establish a standard chart for interpreting logging curves of mudstone and volcanic rock: use the sonic transit logging curve as the abscissa, and the neutron logging curve and density logging curve as the ordinate respectively. Then input the three curve data of the standard layer and the volcanic rock section into the coordinate axis to establish a standard chart for interpreting logging curves.

[0009] (5) Qualitative identification of thin mudstone interlayers inside volcanic rocks: The three logging curves of the igneous rocks for which prediction is needed are standardized according to step (2). The values ​​of the standardized three logging curves are compared with the logging curve interpretation standard chart in step (4) to determine whether there are thin mudstone interlayers inside the volcanic rocks.

[0010] In step (4), a standard chart for interpreting logging curves is established, which can clearly distinguish the boundary between mudstone and volcanic rock.

[0011] The beneficial effects of this invention are: when there is limited logging data, the qualitative identification method for thin mudstone interlayers inside volcanic rocks based on logging curve data can quickly and accurately identify mudstone interlayers developed inside volcanic rocks in a single well, providing scientific decision-making for the effective development of volcanic rocks. Attached Figure Description

[0012] Figure 1 This is a flowchart of the qualitative identification method for thin mudstone interlayers inside volcanic rocks according to the present invention.

[0013] Figure 2 This is a single-well logging curve according to an embodiment of the present invention.

[0014] Figure 3 This is a diagram of the entire stable mudstone section according to an embodiment of the present invention.

[0015] Figure 4A This is a standardized result diagram of neutron logging curves obtained using the method of this invention.

[0016] Figure 4B This is a standardized result diagram of the density logging curve obtained using the method of this invention.

[0017] Figure 4C This is a standard result diagram of the sonic transit time logging curve using the method of this invention.

[0018] Figure 5A It is a standard chart for interpreting acoustic transit time and neutron logging curves obtained using the method of this invention.

[0019] Figure 5B It is a standard chart for interpreting acoustic transit time and density logging curves obtained using the method of this invention.

[0020] Figure 6 This is an interpretation diagram of the single-well interlayer identification results obtained using the method of this invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art without creative effort are within the protection scope of the present invention.

[0022] like Figure 1 As shown, the method for qualitative identification of thin mudstone interlayers within volcanic rocks according to the present invention includes the following steps:

[0023] (1) Selecting the standard layer as the standard logging curve: Based on the core data and logging data, select the mudstone section that is stable throughout the area above the igneous rock section as the standard layer;

[0024] (2) Standardize the logging curves of the standard layer: Statistical analysis is performed on the three logging curves of the standard layer: neutron logging curve, sonic transit time logging curve and density logging curve. The peak value and distribution range of the three logging curves are determined, and the three logging curves of the standard layer are corrected to the same peak value and distribution range.

[0025] (3) Standardize the logging curves of the volcanic rock section: Following the method in step (2), correct the three logging curves of the volcanic rock section to the same peak value and distribution range;

[0026] (4) Establish a standard chart for interpreting logging curves of mudstone and volcanic rock: use the sonic transit logging curve as the abscissa, and the neutron logging curve and density logging curve as the ordinate respectively. Then input the three curve data of the standard layer and the volcanic rock section into the coordinate axis to establish a standard chart for interpreting logging curves.

[0027] (5) Qualitative identification of thin mudstone interlayers inside volcanic rocks: The three logging curves of the igneous rocks for which prediction is needed are standardized according to step (2). The values ​​of the standardized three logging curves are compared with the logging curve interpretation standard chart in step (4) to determine whether there are thin mudstone interlayers inside the volcanic rocks.

[0028] In step (4), a standard chart for interpreting logging curves is established, which can clearly distinguish the boundary between mudstone and volcanic rock.

[0029] Specifically:

[0030] Step 1: Select a logging curve that responds well to the interlayer. This involves two steps.

[0031] (1) Using core and logging data, determine the mudstone section for selecting logging curves: Conduct core observation and combine with existing logging data to determine the distribution of mudstone sections for selecting logging curves with obvious mudstone interlayer responses.

[0032] (2) Selection of logging curves: Select the three curves that have the best response to mudstone (neutron logging curve, sonic transit time logging curve, density logging curve).

[0033] Step 2: Standardize the selected three logging curves, which involves the following three steps:

[0034] (1) Selecting the standard layer as the standard logging curve: Based on the core data and logging data, select the mudstone section that is stable throughout the target layer as the standard layer.

[0035] (2) Standardization of logging curves for standard formations: The three logging curves (neutron logging curve, sonic transit time logging curve, and density logging curve) for the standard formations are calibrated. First, statistical analysis is performed on the three curves for the mudstone formation to determine the peak value and distribution range of the logging curves. Then, the logging curve values ​​are processed by adding or subtracting values ​​from different periods to bring them to a uniform range. The logging curves for the target formation are then calibrated to the same peak value and distribution range.

[0036] (3) Standardize the logging curves of the volcanic rock section: Apply the results of the standard layer logging curve standardization to standardize the logging curves of the target layer.

[0037] Step 3: Qualitatively determine the logging interpretation characteristics of mudstone.

[0038] (1) Selection of sample points for different lithologies: Based on the existing standardized neutron logging curves (CNL), sonic transit time logging curves (AC), and density logging curves (DEN) of thick mudstone in volcanic rock, sample points of logging curves of thick mudstone and other lithologies in the target layer are selected.

[0039] (2) Establishing a logging interpretation chart for mudstone interlayers: The selected mudstone and volcanic rock sample points are used to establish a chart. The coordinate system is projected using sonic transit time logging curves, neutron logging curves, sonic transit time logging curves, and density logging curves respectively, and a logging interpretation chart is established.

[0040] (3) Determine the qualitative identification criteria for mudstone: Analyze the established well logging interpretation charts to determine the critical values ​​that distinguish mudstone from other lithologies, and use these as the identification criteria for mudstone and volcanic rocks.

[0041] Step 4: Predict the interlayers developed between wells

[0042] Based on the different logging curve values ​​in the chart, the lithology of the well is determined, the mudstone interlayers in a single well are qualitatively identified, and the interlayer prediction between wells is completed based on the identification of interlayers in a single well.

[0043] The method of the present invention will be described in detail below with reference to specific embodiments:

[0044] 1. Preliminary data preparation.

[0045] First, 78 wells with complete data suitable for the study were selected. Core and logging data that clearly reflected lithology, as well as representative curves reflecting reservoir properties, including neutron logging (CNL), acoustic transit time logging (AC), and density logging (DEN), were chosen. Figure 2 .

[0046] 2. Select a stable mudstone stratum above the target layer, such as... Figure 3 This section of logging curve was selected as the standard section for logging standardization. The sonic transit time, density logging, and neutron logging curves of all wells in the work area were corrected. The neutron logging curve was corrected to the range of 0–40, the sonic transit time logging curve to the range of 100–500, and the density logging curve to the range of 1–3, ensuring that the three types of curves for different wells have the same value range and peak value. (See Figure 4.)

[0047] Reservoir properties are determined using well logging curves (neutron logging, sonic transit time logging, and density logging) that reflect the reservoir's pore structure. Sonic logging reflects velocity, which is related to the density of the material; the higher the density, the faster the sonic velocity. Density reflects lithology and porosity. Neutron logging is sensitive to hydrogen, thus reflecting porosity. Using these three types of curves together allows for the calculation of relatively accurate lithological parameters.

[0048] 3. Based on the existing mudstone calibration logging curves inside volcanic rocks from core data and well logging data, establish calibration standards for mudstone interlayers inside volcanic rocks, i.e., mudstone interlayer logging interpretation charts.

[0049] Based on the existing neutron logging (CNL), sonic transit time logging (AC), and density logging (DEN) curves of thick mudstone layers within volcanic rocks, sample points of the logging curves in the middle of the thick mudstone layers were selected, and outliers were removed. Two intersection icons of the three logging curves were established as standard charts for interpreting logging curves of mudstone and volcanic rocks, as shown in Figure 5.

[0050] 4. The two obtained well logging interpretation standard charts were used to verify existing interlayers in the core and well logging data. Based on the established well logging interpretation charts, the response characteristics of mudstone interlayers within volcanic rocks on the curves were determined, i.e., the value range corresponding to mudstone in the three types of well logging curves. The lithology in the well was judged according to the different value ranges of the well logging curves in the charts, and the mudstone interlayers in single wells were qualitatively identified. The identification results were then compared with existing mudstone interlayers in well logging data, showing a high accuracy rate. Figure 6 .

[0051] In summary, the content of this invention is not limited to the above-described embodiments. Those skilled in the art can easily propose other embodiments within the technical guiding principles of this invention, but such embodiments are all included within the scope of this invention.

Claims

1. A method for qualitative identification of thin mudstone interlayers within volcanic rocks, characterized in that, Includes the following steps: (1) Selecting the standard layer as the standard logging curve: Based on the core data and logging data, select the mudstone section that is stable throughout the area above the igneous rock section as the standard layer; (2) Standardize the logging curves of the standard layer: Statistical analysis is performed on the three logging curves of the standard layer: neutron logging curve, sonic transit time logging curve and density logging curve. The peak value and distribution range of the three logging curves are determined, and the three logging curves of the standard layer are corrected to the same peak value and distribution range. (3) Standardize the logging curves of the volcanic rock section: Following the method in step (2), correct the three logging curves of the volcanic rock section to the same peak value and distribution range; (4) Establish a standard chart for interpreting logging curves of mudstone and volcanic rock: use the sonic transit logging curve as the abscissa, and the neutron logging curve and density logging curve as the ordinate respectively. Then input the three curve data of the standard layer and the volcanic rock section into the coordinate axis to establish a standard chart for interpreting logging curves. (5) Qualitative identification of thin mudstone interlayers inside volcanic rocks: The three logging curves of the igneous rocks for which prediction is needed are standardized according to step (2). The values ​​of the standardized three logging curves are compared with the logging curve interpretation standard chart in step (4) to determine whether there are thin mudstone interlayers inside the volcanic rocks.

2. The method for qualitative identification of thin mudstone interlayers within volcanic rocks according to claim 1, characterized in that, In step (4), a standard chart for interpreting logging curves is established, which can clearly distinguish the boundary between mudstone and volcanic rock.

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