A data processing method for identifying gas layers in drill collar inelastic gamma ray based on spectrum analysis

Abstract

The present invention provides a data processing method for drill collar non-elastic gamma gas layer identification based on spectrum analysis, the method comprising the following steps: obtaining a formation element non-elastic gamma standard spectrum of a controlled-source gas layer identification device while drilling and an instrument's own non-elastic gamma standard spectrum; establishing a set of water-saturated and gas-saturated formation models, and obtaining total non-elastic gamma energy spectrum information of the device in gas-saturated and water-saturated formations with different porosities; processing the total non-elastic gamma energy spectrum information, and extracting the instrument's own non-elastic gamma spectrum total count from the total non-elastic gamma energy spectrum information; converting the extracted instrument's own non-elastic gamma spectrum total count, and preparing a gas layer identification plate; obtaining the actual formation total non-elastic gamma energy spectrum recorded by the controlled-source gas layer identification device while drilling, despectrating the actual formation total non-elastic gamma energy spectrum, and obtaining the instrument's own non-elastic gamma spectrum total count; comparing the obtained instrument's own non-elastic gamma spectrum total count with the gas layer identification plate, and performing gas layer identification on the actual formation.

Description

Technical Field

[0001] The present invention relates to the field of oil and natural gas development, and in particular to a drill collar non-elastic gamma gas layer identification data processing method based on spectrum analysis. Background Art

[0002] Neutron gas layer identification while drilling plays an important role in oil and gas exploration and development. However, existing thermal neutron and gamma capture gas layer identification technologies are susceptible to the influence of high-capture cross-section elements in the formation. While inelastic gamma ray gas layer identification technology overcomes the influence of high-capture cross-section elements, it is significantly affected by formation density attenuation, which reduces the sensitivity of gas layer identification.

[0003] A Chinese patent, now published under the patent number CN113123779A, discloses a device and method for identifying gas formations while drilling (LWD) based on iron inelastic gamma scattering. This method extracts pure Fe inelastic gamma peak counts instead of high-energy fast neutron information for gas formation identification. This method successfully addresses the significant influence of formation density on inelastic gamma information and improves the sensitivity of gas formation identification. However, pure Fe inelastic peak counts often have poor counting statistics, resulting in significant uncertainty in gas formation identification. Furthermore, while pure Fe inelastic peak counts effectively reduce interference from the inelastic gamma spectrum background, they also result in the loss of effective information and a partial reduction in gas formation sensitivity. Summary of the Invention

[0004] The purpose of the present invention is to address the above shortcomings and propose a drill collar inelastic gamma gas layer identification data processing method that directly obtains the instrument's own inelastic gamma energy spectrum information in a controlled source gas layer identification device while drilling through spectrum analysis technology to identify gas layers.

[0005] The present invention specifically adopts the following technical solutions:

[0006] A data processing method for identifying inelastic gamma gas layers in drill collars based on spectrum analysis comprises the following steps:

[0007] (1) The Monte Carlo numerical simulation method is used to obtain the inelastic gamma standard spectrum of the formation elements of the controlled source gas layer identification device while drilling and the inelastic gamma standard spectrum of the instrument itself.

[0008] (2) A set of water-saturated and gas-saturated formation models with a borehole diameter of 8.75 inches was established using numerical simulation methods to obtain the non-elastic gamma energy spectrum information of the controlled source gas layer identification device while drilling in gas-saturated and water-saturated formations with different porosities.

[0009] (3) Based on the established inelastic gamma standard spectrum of formation elements and the instrument's own inelastic gamma standard spectrum, the total inelastic gamma energy spectrum information recorded by the while-drilling gas layer identification device in water-saturated and gas-saturated formations with different porosities is decoded and analyzed to obtain the total count of the instrument's own inelastic gamma spectrum.

[0010] (4) Based on the actual logging conditions, the total counts of the instrument's own inelastic gamma spectrum obtained by spectrum analysis are converted, and the converted total counts of the instrument's own inelastic gamma spectrum obtained from water-saturated and gas-saturated formations with different porosities are used to produce a gas layer identification chart.

[0011] (5) Obtain the actual total inelastic gamma energy spectrum of the formation recorded by the while-drilling gas layer identification device, and use source strength monitoring information to eliminate the influence of neutron source stability on energy spectrum acquisition; repeat the operation of step (3), deconstruct the total inelastic gamma energy spectrum under actual formation conditions, and obtain the total count of the instrument's own inelastic gamma spectrum under actual formation conditions; compare the actual total count of the instrument's own inelastic gamma spectrum with the gas layer identification plate, and perform gas layer identification on the actual formation.

[0012] Preferably, the controlled-source gas layer identification device while drilling refers to various while drilling instruments equipped with a drill collar, a DT neutron source, a source intensity monitor, and a gamma detector that is far away from the neutron source.

[0013] Preferably, the spectrum solution method in (3) refers to a conventional spectrum solution method such as least squares method, weighted least squares method or non-negative least squares method.

[0014] Preferably, the actual logging conditions in (4) refer to the neutron source stability intensity, logging speed, depth interval, and detector efficiency, and the conversion refers to the total count of the instrument's own inelastic gamma spectrum multiplied by the neutron counting flux under the actual logging conditions.

[0015] Preferably, the source intensity monitoring information in (5) comes from a source intensity monitor, which is used to eliminate the influence of source intensity fluctuations on the total inelastic gamma energy spectrum counts during the actual logging process. The above-mentioned actual formation total inelastic gamma energy spectrum can only be used for spectrum analysis after being processed with source intensity correction.

[0016] The present invention has the following beneficial effects:

[0017] The data processing method for drill collar inelastic gamma gas layer identification based on spectrum analysis processes the total inelastic gamma energy spectrum information of the while-drilling gas layer identification device through spectrum analysis counting, extracts the total count of the instrument's own inelastic gamma spectrum for gas layer identification, solves the problem of poor statistics of the iron peak counting method, and further improves the sensitivity of gas layer identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 Non-elastic gamma ray quasi-spectroscopy for formation elements and controlled source gas layer identification while drilling;

[0019] Figure 2 The inelastic gamma spectrum of 35% porosity water-saturated and gas-saturated sandstone;

[0020] Figure 3 is the ratio of the total count of the instrument's own inelastic gamma spectrum to the total inelastic count;

[0021] Figure 4 This is a gas layer identification chart based on the total count of the instrument's own inelastic gamma spectrum. DETAILED DESCRIPTION

[0022] The specific implementation of the present invention will be further described below with reference to the accompanying drawings and specific embodiments:

[0023] A data processing method for identifying inelastic gamma gas layers in drill collars based on spectrum analysis comprises the following steps:

[0024] (1) Monte Carlo numerical simulation method is used to obtain the inelastic gamma standard spectrum of formation elements of the controlled source gas layer identification device while drilling and the inelastic gamma standard spectrum of the instrument itself. The instrument-formation model of the example while drilling device is established by Monte Carlo numerical simulation method, and the inelastic standard spectrum of common formation elements such as Si, Ca, Mg, C and O of the gas layer identification device while drilling and the inelastic standard spectrum of the instrument itself are simulated, such as Figure 1 shown.

[0025] A controlled-source gas-reservoir identification system (LSRD) for logging while drilling (LWD) refers to various LWD instruments consisting of key components: a drill collar, a DT neutron source, a source intensity monitor, and a gamma detector located at a distance from the neutron source. The gamma detector is located 65 cm from the neutron source. In this example, the LWD process uses a drill collar speed of 60 m / h, a logging depth interval of 12.5 cm, and a stable neutron source intensity of 6.4E+8.

[0026] In actual application, the formation element inelastic gamma standard spectrum and the instrument's own inelastic gamma standard spectrum need to be re-established according to the specific while-drilling gas layer identification device and formation conditions.

[0027] The inelastic gamma standard spectrum of formation elements and the instrument's own inelastic gamma standard spectrum information come from the gamma detector components that are far away from the neutron source.

[0028] The formation element inelastic gamma standard spectrum and the instrument's own inelastic gamma standard spectrum are normalized using the total counts of their respective energy spectra.

[0029] The source intensity monitor can be a component that records the current and voltage of the DT neutron source, or it can be a gamma or neutron detector close to the neutron source, used to monitor the changes in the neutron source intensity over time.

[0030] (2) A numerical simulation method was used to establish a set of water-saturated and gas-saturated formation models with a wellbore diameter of 8.75 inches, and the non-elastic gamma energy spectrum information of the controlled source gas layer identification device while drilling in gas-saturated and water-saturated formations with different porosities was obtained.

[0031] The upper inelastic gamma-ray spectrum information comes from ideal simulation conditions without the influence of neutron source intensity variation.

[0032] The total inelastic gamma spectrum contains a large proportion of the instrument's own inelastic gamma spectrum. This is because the drill collar and the instrument housing are close to the neutron source and occupy a large proportion in the wellbore space.

[0033] Using the controlled neutron source while drilling instrument-formation model, a set of gas-saturated and water-saturated sandstone formation models were set up, with formation porosities of 0%, 1%, 5%, 10%, 15%, 20%, 25%, 30%, and 35% respectively; the total inelastic gamma spectroscopy information collected by the gas layer identification device while drilling in water-saturated and gas-saturated formations with different porosities was simulated. Figure 2 The total inelastic gamma spectra of gas-saturated and water-saturated sandstones with a porosity of 35% are shown.

[0034] (3) Based on the established inelastic gamma standard spectrum of formation elements and the instrument's own inelastic gamma standard spectrum, the total inelastic gamma energy spectrum information recorded by the while-drilling gas layer identification device in water-saturated and gas-saturated formations with different porosities is decoded and analyzed to obtain the total count corresponding to the instrument's own inelastic gamma spectrum.

[0035] Spectral decomposition methods include conventional methods such as least squares, weighted least squares, or non-negative least squares. The total count of the instrument's own inelastic spectrum is not subject to significant error because the instrument's own inelastic gamma energy spectrum accounts for a large proportion of the total inelastic gamma energy spectrum. Conventional spectral decomposition methods can produce relatively accurate results.

[0036] Taking sandstone formation as an example, the total counts of the instrument spectrum after spectrum analysis account for about 20% to 45% of the total non-elastic counts, which is quite considerable and can be used for gas layer identification without large errors. Figure 3 .

[0037] (4) Based on the actual logging conditions, the total counts of the instrument's own inelastic gamma spectrum obtained by spectrum analysis are converted, and the gas layer identification chart is made using the converted total counts of the instrument's own inelastic gamma spectrum obtained from water-saturated and gas-saturated formations with different porosities. Figure 4 , this plate is the actual sandstone formation gas layer identification plate.

[0038] Table 1 shows the results of processing inelastic gamma ray spectra for water- and gas-saturated formations of varying porosity using both the Fe peak counting method and the spectral analysis method. As shown in Table 1, the total instrument-derived inelastic gamma ray counts obtained using the spectral analysis method are approximately 300 to 400 times higher than the Fe peak counts, demonstrating the statistical superiority of the spectral analysis method.

[0039] Table 1 Statistical comparison of spectrum analysis counting and iron peak counting data

[0040]

[0041] The actual logging conditions refer to the stable intensity of the neutron source, logging speed, depth interval, detector efficiency, etc. The conversion refers to the total count of the instrument's own inelastic gamma spectrum multiplied by the neutron counting flux under the actual logging conditions.

[0042] Table 2 shows the difference in gas layer identification sensitivity between the Fe peak counting method and the spectrum analysis method. As shown in Table 2, under normal porosity conditions, the spectrum analysis method is generally more sensitive to gas layer identification than the Fe peak counting method.

[0043] Table 2 Comparison of gas layer identification sensitivity between iron peak counting and spectrum analysis

[0044]

[0045] (5) Obtain the actual total inelastic gamma energy spectrum of the formation recorded by the while-drilling gas layer identification device, and use source strength monitoring information to eliminate the influence of neutron source stability on energy spectrum acquisition; repeat the operation of step (3) to deconvolve the actual total inelastic gamma energy spectrum of the formation and obtain the total count of the instrument's own inelastic gamma spectrum under actual formation conditions; compare the total count of the instrument's own inelastic gamma spectrum under actual conditions with the gas layer identification plate to identify the gas layer in the actual formation.

[0046] The above-mentioned source intensity monitoring information comes from the source intensity monitor and is used to eliminate the influence of source intensity fluctuation on the total inelastic gamma energy spectrum count during the actual logging process. The above-mentioned actual formation total inelastic gamma energy spectrum can only be used for spectrum analysis after being processed by source intensity correction.

[0047] Of course, the above description is not a limitation of the present invention, and the present invention is not limited to the above examples. Changes, modifications, additions or substitutions made by technicians in this technical field within the essential scope of the present invention should also fall within the scope of protection of the present invention.

Claims

1. A data processing method for identifying inelastic gamma gas layers in drill collars based on spectrum analysis, characterized in that: The following steps are involved: (1) Monte Carlo numerical simulation method is used to obtain the inelastic gamma standard spectrum of formation elements of the controlled source gas layer identification device while drilling and the inelastic gamma standard spectrum of the instrument itself. The controlled source gas layer identification device while drilling refers to various types of drilling instruments equipped with a drill collar, a DT neutron source, a source intensity monitor, and a gamma detector that is far away from the neutron source; (2) Using numerical simulation methods, a set of water-saturated and gas-saturated formation models with a borehole diameter of 8.75 inches was established to obtain inelastic gamma spectroscopy information of the controlled source gas layer identification device while drilling in gas-saturated and water-saturated formations with different porosities; (3) Based on the established inelastic gamma standard spectrum of formation elements and the instrument's own inelastic gamma standard spectrum, the total inelastic gamma energy spectrum information recorded by the controlled source gas layer identification device while drilling in water-saturated and gas-saturated formations with different porosities is decoded and analyzed to obtain the total counts corresponding to the instrument's own inelastic gamma spectrum under the conditions of water-saturated and gas-saturated formations with different porosities; (4) Based on the actual logging conditions, the total counts of the instrument's own inelastic gamma spectrum obtained by spectrum analysis are converted, and the converted total counts of the instrument's own inelastic gamma spectrum are used to produce a gas layer identification chart; (5) Obtain the total inelastic gamma energy spectrum under actual formation conditions recorded by the controlled source gas layer identification device while drilling, and use source strength monitoring information to eliminate the influence of neutron source stability on energy spectrum acquisition; repeat the operation of step (3), deconstruct the total inelastic gamma energy spectrum under actual formation conditions, and obtain the total count of the instrument's own inelastic gamma spectrum under actual formation conditions; compare the total count of the instrument's own inelastic gamma spectrum under actual conditions with the gas layer identification plate, and perform gas layer identification on the actual formation.

2. The method for processing drill collar inelastic gamma gas layer identification data based on spectrum analysis according to claim 1, characterized in that: The stratigraphic model lithology in (2) includes not only sandstone, limestone, and dolomite, but also varies according to the geochemical characteristics of the region.

3. The method for processing drill collar inelastic gamma gas layer identification data based on spectrum analysis according to claim 1, characterized in that: The spectrum solution method in (3) refers to the least square method, the weighted least square method or the non-negative least square method.

4. The method for processing drill collar inelastic gamma gas layer identification data based on spectrum analysis according to claim 1, characterized in that: The actual logging conditions in (4) refer to the neutron source stability intensity, logging speed, depth interval, and detector efficiency. The conversion refers to the total count of the instrument's own inelastic gamma spectrum obtained by spectrum decomposition multiplied by the neutron counting flux under the actual logging conditions.

5. The method for processing drill collar inelastic gamma gas layer identification data based on spectrum analysis according to claim 1, characterized in that: The source intensity monitoring information in (5) comes from the source intensity monitor and is used to eliminate the influence of source intensity fluctuation on the inelastic gamma energy spectrum count during the actual logging process. The above-mentioned actual formation total inelastic gamma energy spectrum can only be used for spectrum analysis after being processed by source intensity correction.

Images