CN111472760A - Novel method for extracting related flow well logging tracing peak - Google Patents
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Abstract
The invention relates to a new method for extracting a related flow logging tracing peak, which is an effective means for determining an injection profile of a water injection well by related flow logging. The method comprises the following specific steps in sequence: (1) extracting background area data; regions that do not contain trace peaks are selected to constitute a new sequence. (2) Estimating the noise level; and obtaining smooth estimation of a background sequence through filtering processing, estimating noise variance through the smooth estimation, and extracting a tracing peak area by using a 3sigma criterion. (3) And positioning the tracing peak by a maximum likelihood method. In order to prevent overlapping peaks in the peak region caused by uniform distribution of the tracer, the peak region is adjusted by introducing parameters, and the peak position is identified again. The method combines the noise characteristics and the tracing peak distribution characteristics to realize elimination of false peaks, eliminates overlapped peaks by setting parameters, and accurately positions the peak positions of the tracing peaks by adopting a maximum likelihood estimation method, thereby finally laying a foundation for related flow logging interpretation.
Description
Technical Field
The invention relates to a method for extracting a related flow logging tracing peak, in particular to the identification and extraction of the related flow logging tracing peak under low signal-to-noise ratio. Based on the noise characteristics of the measurement signals and the principle of the maximum likelihood method, the related flow tracing peak can be effectively identified and positioned, and the method has good noise immunity and capability of identifying false peaks, and is a related flow logging data processing method with higher precision.
Background
As most onshore oil fields gradually enter the middle and later development stages, the improvement of oil well recovery rate becomes an important subject in the development of the oil fields at present. The water injection development of the oil well is one of the commonly adopted methods when the oil field carries out secondary oil recovery, and the formation pressure is maintained in a layered water injection mode. Therefore, the dynamic state of the water injection well can be known in time, the water absorption condition of each layer can be accurately described, and the quantitative determination of the water absorption profile of the water injection well section is very important.
The related flow logging is a commonly used dynamic monitoring logging method for a water absorption profile, and the technology mainly tracks and measures the flow velocity of a liquid tracer agent and is assisted by parameters such as flow, well temperature, pressure and the like, so that the water absorption condition of a distribution injection well section can be comprehensively analyzed. Correlated flow water absorption profile logs can reflect the distance between the detector and the tracer bolus by recording gamma photons generated by radioactive decay of the tracer. When the radiotracer is in close proximity to the detector, the detector will produce a corresponding output signal. When the radioactive material is released into the wellbore through the releaser, the tracer flows in a concentrated form with the well fluid. When the detector passes through two detectors at a certain distance, the detector has obvious change signals, and the waveform of the detector in a time-counting rate coordinate system changes obviously. The time interval between the radioactive material flowing through the two detectors can be determined by analysis, and if the distance between the detectors is known, the flow rate of the fluid can be calculated.
When the related flow logging technology is used for measurement, firstly, the tracer is released into a shaft through the releaser, the tracer is continuously tracked by lifting or lowering the instrument, signals received by the gamma detector are gradually enhanced when the instrument is gradually close to the tracer, and signals received by the gamma detector far away from the tracer are gradually weakened, so that a peak signal is formed. During measurement, the instrument firstly lifts and penetrates through the tracer group liquid and then descends and penetrates through the tracer group liquid; or the gamma probe receives two peak signals successively after the gamma probe is lifted up and passes through the tracer group liquid after the tracer group liquid is put down. Therefore, the moving speed and direction of the tracer liquid can be determined by comparing the depth difference and the time difference of the two tracer peaks, namely the water flow speed and direction of different spaces of the shaft. And the water flow can be determined by combining the sectional area of the shaft, so that the water absorption profile can be determined. Therefore, the accurate determination of the peak position of the tracer peak is a precondition for the related flow logging interpretation and is also a basis for describing the water absorption profile.
Disclosure of Invention
The invention aims to provide a method for extracting a tracing peak of related flow logging data, which is used for identifying and positioning a true peak recorded in the logging data and eliminating the influence caused by a false peak, thereby laying a foundation for the quantitative calculation of an injection profile. The interpretation accuracy of the correlated flow log is improved. In order to achieve the above technical object, the present invention provides the following technical solutions.
The extraction method of the related flow logging tracing peak comprises two main steps: 1. and identifying peak areas. And eliminating false peaks generated by noise from the logging signals to obtain a peak area of a real tracing peak. 2. And (5) positioning the peak position. And accurately positioning the peak position in the identified peak area by adopting a maximum likelihood method. The theoretical principle and the specific implementation of the two steps are explained in detail below.
1. Peak region identification
For correlated flow logging, the acquired signal usually includes three parts, namely a tracer peak signal, a background signal and a noise signal. Because the tracer is radioactive, the count rate recorded by the probe increases when the instrument probe is close to the tracer and decreases when the probe is further from the tracer. When the probe is far enough away from the tracer, the signal measured by the instrument is mainly a natural background and a noise signal. The natural background can be generally regarded as a relatively stable constant value, while the noise signal is unavoidable in the measurement process, mainly caused by radioactive statistical fluctuation and instrument stability, and the noise signal usually forms a large number of false peaks due to its randomness, but the count rate of the noise signal is generally lower than that of the tracing peak signal. In addition, because the instrument repeatedly passes through the tracer in the measurement process, tracer peaks repeatedly appear in the measurement signal, and a background signal exists between the two tracer peaks. Whereas noise signals are present over the entire measuring signal range.
Based on the analysis, the premise of tracing peak extraction is to eliminate the adverse effect caused by noise and prevent the occurrence of false peaks. Therefore, it is first necessary to determine the range of the peak region where the true peak is located when performing the extraction. The method for realizing the peak area identification comprises the following steps:
(1) background region truncation and assembly
Due to the repeated up-and-down measurement mode of the correlation flow logging, a section of background area exists between the two tracing peaks, and due to the fact that the background signal is approximately constant, data in a plurality of background areas are selected and combined together, and therefore the noise level can be estimated.
(2) Estimating measurement data noise level
In order to effectively estimate the total noise level of the signal, based on the basic principle of the common abnormal point identification method, namely the 53H method, firstly, a smooth estimation of the pure background signal is obtained. The background signal smooth estimation can be realized by performing 5-point median filtering, 3-point median filtering and Hanning filtering on the intercepted signal segment, and the method comprises the following specific steps of:
(a) assuming that the data sequence is x (i), a new sequence x ' (i) is constructed from this sequence by taking the median of x (1), …, x (5) as x ' (3), then truncating x (1), adding x (6) and taking the median x ' (4), and so on until the last data is added. In summary, the median value was chosen among 5 adjacent data. Obviously, x' (i) has 4 fewer terms than x (i).
(b) A similar approach is used to select the median of 3 adjacent data in x' (i) to form the sequence x "(i).
(c) The sequence x '(i) was processed using a Hanning smoothing filter as shown in equation 1 to obtain the sequence x' (i):
x″′(i)=0.25x″(i-1)+0.5x″(i)+0.25x″(i+1) (1)
the sequence x' "(i) is a smoothed estimate of the original sequence. The difference between the original sequence and the smoothed estimate sequence reflects the level of noise. Therefore, the calculation can be performed by using the equation (2).
d(i)=|x(i)-x″′(i)| (2)
In order to quickly calculate the noise level, the invention adopts a robust median estimation method to calculate the standard deviation of the noise. For a signal sequence in which the number of bits can be regarded as a robust estimate of the mean, equation (3) can be used to calculate the noise standard deviation
σ=median(d)/0.6745 (3)
For noise, due to its randomness, its amplitude is usually small compared to the trace peak, which is usually greater than the sum of three standard deviations of the background and the noise according to the 3sigma principle, so that the peak area can be screened using this criterion.
(3) Peak data point determination
As previously mentioned, the background signal of the associated flow measurement data can be generally considered to be a constant, and thus, the average of the smoothed estimates of the truncated data can be used to estimate the magnitude of the background. Comparing the value of each point in the original measurement data with the value of 3 times standard deviation of noise, and if the value in the original data satisfies formula (4), judging the data point as a peak area.
x(i)>3σ+mean(x″′) (4)
The judgment standard of the formula (4) can be used for extracting a plurality of sections of tracing peak regions from an original signal sequence, and non-peak regions can be effectively removed.
2. Peak location
All potential tracing peak positions can be extracted through peak area identification, and next step needs to extract accurate peak positions of tracing peaks in each peak area. The related flow logging tracing peak theoretically accords with Gaussian distribution and has the characteristic of a Gaussian function. Therefore, according to the mathematical characteristics of the tracing peak, the invention adopts a maximum likelihood estimation method to estimate the peak position.
The maximum likelihood estimation method is to obtain the estimation quantity of an unknown parameter p according to the specific situation of a sample under the condition that the overall form is knownThe expression of the gaussian distribution is shown in formula (5).
In the formula, xi-the abscissa index;
p (i) -amplitude of trace peak on trace i;
c-peak position of tracing peak;
μ — standard deviation of trace peak, proportional to peak width;
h-peak height of tracing peak.
When the maximum likelihood estimation method is used, a likelihood function needs to be constructed firstly, and the likelihood function of the Gaussian function is shown as a formula (6).
In order to estimate the peak position accurately, the partial derivative of the likelihood solving function to μ is required, and for convenience of calculation, logarithms are taken on two sides of equation (6), as shown in equation (7).
When the partial derivative of the likelihood function to mu is 0The solution at this time is the best estimate of the peak position, as shown in equation (8).
It can be seen that the estimation of the peak position can be regarded as a weighted average of the count rate and the time in the peak region.
In practical measurements, due to uneven distribution of the tracer in the injected water stream, a group of overlapping peaks exist in the same peak area, and the group of overlapping peaks generally comprises a main peak and one or more sub-peaks. Usually, the peak position of the main peak represents the true peak position of the tracer peak, but the whole peak region no longer presents a standard gaussian shape due to the existence of the sub-peak, so that the peak region needs to be corrected. The invention realizes the correction of the peak area by setting parameters. The main realization method is to count the number of data points which are greater than the count of the current peak value, if the number of the counted data points is greater than the set parameter, the count of the current peak value is used as a new peak area to determine a threshold value, the peak area is divided again, and the maximum likelihood estimation method is adopted again to estimate the peak position in the newly divided peak area again.
The invention provides a method for extracting a related flow tracing peak, which firstly extracts a peak area range of the tracing peak according to the technical characteristics of related flow logging and the characteristics of noise, thereby eliminating the false peak generated by the noise. And determining the peak position of the tracing peak by adopting a maximum likelihood estimation method based on the distribution form of the tracing peak. In order to eliminate the overlapped peak of the tracer in the water flow caused by uneven distribution, the invention introduces a parameter, and realizes the correction of the current peak area by counting the number of data points of counting rate greater than the current peak position and combining the parameter. Once the peak is corrected, the peak position is again determined by maximum likelihood estimation. The invention can accurately extract the tracing peak position and lays a foundation for determining the injection profile of the related flow logging.
Compared with the prior art, the invention has the remarkable advantages that: (1) the method has good noise resistance, and can effectively eliminate adverse effects caused by noise and radioactivity statistical fluctuation. The true tracer peak is retained by estimating the standard deviation of the noise and combining the 3sigma criterion to eliminate the false tracer peak generated by the noise. (2) The method has higher precision, and adopts a maximum likelihood method to estimate the peak position of the tracer peak according to the distribution form of the actual tracer peak. (3) The method has high operation efficiency and can quickly process a large amount of related flow tracing data.
Drawings
FIG. 1 is a schematic view of the process of the present invention
FIG. 2 is a diagram of background region selection effect in an example
Fig. 3 is a graph showing the effect of peak extraction in the example.
FIG. 4 is a graph showing the effect of peak location of tracer peaks in examples.
FIG. 5 is an example well data production profile interpretation.
FIG. 6 is an example well water flow velocity calculation.
Detailed Description
Application example:
the XX well is a water injection development well, the measuring well section of the well is 1920m-2002m, the diameter of a sleeve is 139.70mm, the depth of the sleeve is 2049.98m, the diameter of an oil pipe is 62mm, the depth of the oil pipe is 1983.70m, and the daily water injection amount is 17.45 square/day. The artificial well bottom 2042.25 m. The well adopts a combined injection water injection mode, the oil pressure is 19.00MPa, and the casing pressure is 18.50 MPa. The perforated interval of the well is 1993m-2000m, and the flare is located at 1987 m. The water injection well adopts a related flow logging technology to monitor an injection profile.
The invention is adopted to carry out tracing peak extraction and well logging interpretation on related flow well logging data. First, the logging data of the background area is extracted for noise level estimation, as shown in fig. 1. The potential peak area of the tracer peak in the log data is extracted according to the noise level, as shown in fig. 2, a total of 37 tracer peak areas are extracted, and it can be seen that a part of the peak areas contain overlapping peaks. It is therefore necessary to repartition the region containing the overlapping peaks. The maximum likelihood estimation method is adopted and the setting parameters are combined to realize the accurate positioning of the peak position, as shown in fig. 3, for the sake of clarity, fig. 3 only shows a part of the peak position, so that each peak position can be accurately extracted and the influence of the overlapped peaks is eliminated.
In the related flow logging, on the premise of stable water injection quantity, the fluid speed is calculated according to the distance of tracer slug displacement and the time required by the slug displacement, namely the depth difference of the peak value and the time difference of the peak value. The flow rate is calculated by the following method:
the corresponding flow rate can be calculated by multiplying the cross-sectional area of the pipe string by the flow velocity. And the direction of the velocity of the water flow may be based on the following decision criteria:
1) if T1< T2, and D2> D1, then water flows downward;
2) if T1< T2, and D2< D1, then the water flows upward;
3) if T1> T2, and D2> D1, then the water flows upward;
4) if T1> T2, and D2< D1, the water flows downward.
Wherein T1 and T2 are the peak position time of tracer peak 1 and tracer peak 2; d1, D2 are the peak depths of trace peak 1 and trace peak 2.
Fig. 6 shows the calculation of water flow velocity and flow rate at different depths, the judgment of flow space, and the tracing peak used by each measuring point. The water absorption of the perforation horizon can be finely explained according to the calculation result, the explanation result is shown in table 1, and the corresponding injection profile achievement diagram is shown in fig. 6.
TABLE 1XX well-related flux water absorption Profile interpretation results
Claims (3)
1. A new method for extracting a related flow logging tracing peak sequentially comprises the following steps:
(1) intercepting a portion of the background data in the correlated flow log data for estimation of a noise level;
(2) obtaining smooth estimation of background data by adopting a filtering mode, and then obtaining a noise standard deviation by utilizing a difference value of the smooth estimation data and the original background data;
(3) extracting a tracing peak area in the related flow data based on a 3sigma criterion;
(4) positioning the tracing peak position in the peak area by adopting a maximum likelihood estimation method;
(5) and judging whether overlapping peaks exist in the peak area according to the set parameters, if so, re-dividing the peak area, and positioning the peak position by adopting a maximum likelihood estimation method again.
2. The method of extracting correlation flow trace peak according to claim 1, wherein the step (2) calculates the noise standard deviation by using the following formula:
d(i)=|x(i)-x″′(i)| (1)
σ=median(d)/0.6745 (2)
wherein x (i) -raw correlated flow log data;
x' (i) -correlating the flow log data smoothing estimate sequence;
d (i) -the difference between the original log data and its smoothed estimate sequence;
σ — noise standard deviation.
3. The method according to claim 1, wherein the step (5) includes readjusting the peak area by using an iterative method, setting a parameter N, determining the peak position for the first time by using a maximum likelihood estimation method, if the number of data points in the peak area greater than the current peak position count is greater than N, selecting the data points greater than the threshold value as the threshold value, forming the peak area, and locating the peak position by using the maximum likelihood estimation method again.
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