application of acoustic positioning network in 3d seismic … deng yuanjun et al., application of...

CHINA PETROLEUM EXPLORATION

Volume 21, Issue 2, March 2016

Received date: 27 May 2015; Revised date: 03 Nov. 2015. Corresponding author. E-mail: [email protected] Copyright © 2016, Petroleum Industry Press, PetroChina. All rights reserved.

Application of acoustic positioning network in 3D seismic exploration with an offshore streamer

Deng Yuanjun1, Qiao Xiuhai2, Li Jiang3, Wang Zhe1

1. Pipeline Engineering & Construction Company, CNOOC Energy Technology & Services Limited;

2. China Oilfield Services Limited;

3. CNOOC (China) Tianjin Branch

Abstract: Application shows that the acoustic positioning network is affected by environment, professional equipment, process-

ing methods and artificial factors when it is used for 3D seismic exploration of offshore streamer. In such a case, the accuracy of

acoustic positioning is reduced, and thereby the quality of seismic data is spoilt. In this paper, some methods for optimizing and

improving the acoustical node spacing arrangement, threshold selection, interpolation processing and network adjustment were

proposed after the acoustic positioning networks in several offshore seismic areas were investigated. Practice has proved that

these methods can reduce the outside effect on acoustic positioning networks, improve the positioning accuracy of streamer

acoustic positioning networks, and provide high-quality seismic data.

Key words: offshore, streamer, 3D seismic, acoustic positioning network, effect, analysis

In 3D seismic exploration of offshore streamer, an acous-tic positioning network is used to pinpoint the geophone on the cable[1]. With this technique, the acoustic birds on the cable is used to send and receive acoustic signals, which are then converted into the distances among the acoustic birds, and under the co-action of other professional devices like a compass bird and relative global positioning system (RGPS), the real-time position of geophone on the mobile cable is calculated and derived in real-time. Previously, the 3D seismic exploration of offshore streamer only towed 3 or 4 cables, the underwater acoustic positioning network only consisted of front and end acoustic positioning networks, and there were only a few dozen underwater positioning nodes. As the seismic technique of streamer develops[2], the 3D seismic exploration streamer can tow as many as 14 ca-bles. The front and end acoustic positioning network has gradually been replaced by front, middle and end acoustic positioning network, or even full acoustic positioning net-work, and the underwater positioning nodes have been in-crease by somewhere around several hundreds to a thousand. As the towed cables, cable length and geophones on the ca-ble increase, the underwater positioning nodes increase, the streamer acquired data become more abundant[3], and the seismic acquisition operation of streamer becomes more and more difficult. The trouble comes in how to pinpoint the thousand of underwater nodes. Among the existing seismic techniques of streamer, the acoustic positioning network is irreplaceable. It satisfactorily solves the difficulty of un-derwater geophone positioning through the very existence of the streamer. Furthermore, the acoustic positioning net-

work is improved, the acoustic control system is optimized, and the acoustic equipment performance is upgraded. Inevitably, the acoustic positioning network will become more and more refined.

1. Principles of acoustic positioning network

1.1. Introduction of acoustic networks

There are 3 kinds of acoustic networks:[4], 1) the front and end acoustic positioning network, which consists of acoustic birds at front and end of multiple cables (Fig.1), 2) the front, middle and end acoustic positioning network, which consists of acoustic birds at front, middle and end of multiple cables at a certain distance (Fig.2), and 3) the full acoustic positioning network, which consists of acoustic birds from front to end of each cable at a fixed distance (Fig.3).

1.2. Positioning principles

Acoustic positioning networks, which are based on the circle-circle positioning principle, is a distance positioning system. Specifically, in a three-dimensional space, if the coordinates of 4 points and the distances from them to the target point are known, the circle-circle positioning formula can be used to figure out the coordinate of the target point[5].

Given that the coordinate of pinger A1 is (x1, y1, z1), the coordinates of pingers A2, A3 and A4 are (x2, y2, z2), (x3, y3, z3) and (x4, y4, z4) respectively, and acoustic receiver A0 is installed at the positioning target. When t=0, pinger A1 transmits A band acoustic wave. At the next moment,

2 CHINA PETROLEUM EXPLORATION Vol. 21, No. 2, 2016

Fig. 1 Front and end acoustic positioning network

G1T1 - Acoustic probe above source 1; G2T1 - Acoustic probe above source 2

Fig. 2 Front, middle and end acoustic positioning network

Fig. 3 Full acoustic positioning network

acoustic receiver A0 picks up acoustic wave A, and trans-mits outwards B band acoustic wave. When t=t1, t2, t3 and t4, pingers A1, A2, A3 and A4 pick up acoustic wave B suc-cessively. The distance from A1 to A0 (r1) can be figured out by Eq.(1), the distances from A2, A3 and A4 to A0 (r2, r3, r4) can be figured out by Eq.(2), and then, the coordinate of acoustic receiver A0 (x,y,z) can be figured out by cir-cle-circle positioning formula (3)[6].

r1 = v t1/2 (1) ri = v (ti t1)/2 (i = 2, 3, 4, …, n) (2)

(x xi)2 + (y yi)

2 + (z - zi)2 = r i

2 (i = 1, 2, 3, …, n) (3) where, v - velocity of acoustic wave in sea water, m/s;

r - distance from pinger (receiver) to acoustic trans-ponder, m;

t - time of acoustic wave travelling from pinger (re-ceiver) to acoustic transponder, s.

2. Factors affecting acoustic positioning net-work

2.1. Acoustic network selection

Every acoustic bird in the acoustic positioning network is normally used as an acoustic node, and the distances ob-

tained at each node distribute like branches. Specifically, there are 8 branches at 1 node. In other words, every pinger (receiver) can transmit/receive signals to/from a maximum of 8 acoustic birds, and every acoustic bird can be set as only transmitting, only receiving, or receiving and transmit-ting signals[7]. Therefore, the selection of an acoustic net-work focuses on the configuration of an acoustic network.

Generally, the selection of a front and end acoustic posi-tioning network or front, middle and end acoustic position-ing network depends on the cable length. When the cable length is shorter than 3000 m, the front and end acoustic po-sitioning network is usually adopted. When the cable length is longer than 3000 m, the front, middle and end acoustic positioning network is normally adopted. Whether the front and end acoustic positioning network or the front, middle and end acoustic positioning network is adopted, the posi-tioning accuracy of the cable segment within the acoustic positioning network is higher than that without an acoustic positioning network. As for the cable segment without an acoustic positioning network, the geophone position can only be derived from the position of accurate fore and aft nodes with the help of compass birds, which would inevita-bly result in accuracy errors. As the derivation distance

Deng Yuanjun et al., Application of acoustic positioning network in 3D seismic exploration with an offshore streamer 3

grows the errors would become larger and larger. For the full acoustic positioning network, the acoustic birds distrib-ute more evenly across each cable, and with regards to configuration, it ensures the cable will have consistent posi-tioning accuracy from its front to its end.

2.2. Acoustic data acquisition

There are primarily two factors influencing the acquisi-tion of acoustic data. One is the failure of an acoustic bird, and the other is the transmission of acoustic data in sea wa-ter. The failure of an acoustic bird typically occurs when an acoustic bird has insufficient power, causing a break in communication amongst acoustic birds or with the loss of acoustic bird from the cable, which directly reduces the number of transmitting (receiving) acoustic data, thereby reducing the number of iterations and the total data involved in redundant computation, reducing the acoustic positioning accuracy. The transmission of acoustic data in sea water is mainly affected by external environments, e.g., large surge, shallow water and hard seabed, turbid sea water, coral reef, and island, all of which cause the acquired acoustic data to have large values and outliers; this impacts data processing at a later stage. In addition, if the offset is small, the air bubbles generated by the source and the propeller would af-fect the quality of acoustic data acquired at the fronts of cables.

2.3. Acoustic data processing

Acoustic data processing includes threshold processing, filtration, interpolation, raw data correction, etc.[8]. It is the most critical step of the acoustic positioning network tech-nique, and also represents maximum artificial intervention. At this stage, even an experienced senior operator may make an error in judgment. Fundamentally, he/she not only needs to have abundant experiences in acoustic data proc-essing, but also needs to conduct analysis and make judg-ments combined with the particular circumstances at the time of acquisition. Corresponding thresholds should be se-lected for processing based on the dynamic height at the time of acquisition. When the dynamic is high, fewer interpolated and extrapolated data is better. When the dy-namic is low and the cable variation is gentle, the full set of interpolated and extrapolated data can be properly added, which would not affect the positioning accuracy.

3. Application

In a 3D seismic work area in the northeast of the Bohai Sea, the cable was 4800 m long, the cable depth was 7 m, and the cable was configured with acoustic birds, compass

birds and lateral controllers. In the work area, the water was 1030 m deep, and the tidal oscillation is a semidiurnal tide consisting of 5 rising tides, 6 falling tides and 1 slack tide. South wind or southwest wind was predominant in the spring and summer, while northwest wind or northeast wind in autumn and winter. Fishery activity was frequent within the work area, and there were obstacles like abandoned wreck, shoal, weather vane, jar net and platform in and around the work area.

The work area was a complicated environment in which to try and accurately position an acoustic network, and the full acoustic positioning network was configured as shown in Fig.3. An acoustic bird was configured from front to end of each cable at an interval of 300 m to compose a full acoustic positioning network.

3.1. Setup of acoustic node spacing

Once the acoustic positioning network configuration was determined, the acoustic transmission range of the nodes in the acoustic positioning network was automatically gener-ated[9]. For instance, the adjacent cable spacing in the work area was 100 m, and the adjacent acoustic bird spacing along the cable was 300 m. Once the network configuration was determined, the distance among acoustic nodes was the same as the theoretical spacing value. However, in the ac-quisition operation of streamer, the cable spacing did change with the tidal flow. When the actual spacing was bigger than the theoretical spacing, acoustic data could not be effectively transmitted (received) among acoustic birds. In order to ensure the data was acquired normally among acoustic birds, the transmission range among the acoustic nodes had to be manually adjusted. Usually, the signal transmission range among the nodes was adjusted to the maximum range 600 m, which would guarantee the normal transmission of acoustic data among the acoustic nodes, as well as reduce the effect of outliers to some extent.

3.2. Analyses of oceanic conditions and environment

Water depth and submarine environment had important effect on the acquisition of acoustic data. Taking 1 repre-sentative acquisition line in the work area for example, the acoustic data acquired in real-time (at a depth of 12 m and 25 m) are as shown in Fig.4 and Fig.5, respectively. Green represents that the two-way acquisition of the acoustic nodes was normal. White represents that the one-way acqui-sition was normal. Red represents that the calculated and observed values are largely different or there was no acous-tic data between two acoustic nodes. Comparison between Fig.4 and Fig.5 shows that acoustic data acquired (as shown in Fig.5) was superior to that in Fig.4. After correlational


Fig. 4 Acoustic data of a shallow water zone

Fig. 5 Acoustic data of a deep water zone

analysis on several survey lines adjacent to this line, it was discovered that the acoustic data as shown in Fig.4 was ac-quired in a shallow water zone where there is shoal and the seabed is hard. This resulted in the generation of many acoustic reflected values and affected the quality of acoustic data acquired in real-time. Usually, poor oceanic conditions will affect the positioning accuracy of acoustic network and can generate surge noise, seriously affecting the quality of data. In this situation the acquisition operation should be halted. The submarine environment is uncontrollable, therefore, efforts should be redirected to equipment to en-

sure the acoustic equipment performs properly so as to pro-vide sufficient acoustic observation for the positioning nodes.

3.3. Analysis of defective equipment

Defective equipment typically occurs in one of two ways. First is the failure of acoustic equipment, such as the failure of an acoustic probe, insufficient battery power, the physical entrapment of an acoustic bird (i.e. on a fishnet) and the loss of its retaining ring. The other possibility is the failure of the control system. For instance, a system failure may occur


when a mobile hard disk or USB flash disk is inserted or when the computer is infected by a virus. Therefore, during the acquisition operation, it is recommended that all external equipment be used on the control system’s host, and main-taining an internet connection is avoided.

3.4. Analysis of acoustic data processing

3.4.1. Threshold selection Common threshold processing consists of median thresh-

old, moving median threshold, and variance ratio threshold. The streamer operation is characterized by mobility and real-time performance. Therefore, at the time of threshold processing an appropriate threshold should be selected, based on the acoustic observation data variation characteris-tics of each survey line. This is the only method available for obtaining optimal results, thus the processing personnel must have adequate experience and ability. For example, if an acoustic bird acquires a group of observation values, i.e. 105.8, 105.9, 106, 106.5 and 1500, the median is 106, and the mean is 384.8. It can be determined that 1500 is a sharp jump and that 106 is more appropriate to use to eliminate the gross error than 384.8. In such a case it is more suitable to select a median threshold than to select two other types of thresholds since the median is not affected by the large sharp jump within the sampling interval. Similarly, since the acoustic observation data is generally stable and with mini-mal changes along the direction of the cable, the selection of a median threshold allows for optimum processing potential. Under poor oceanic conditions, the variance dynamics of acoustic data should be observed. If the variation is large and the dynamic is high, the selection of a variance ratio threshold can better eliminate the gross errors and retain more and effective observation values. 3.4.2. Interpolation processing

Interpolation is used as a supplement whenever any ob-

servation value is absent in (or at both ends of) the data ac-quired between any two acoustic nodes, when the acquisi-tion through every seismic line is completed. The effect of interpolation processing primarily occurs in one of two ways. The first is in the selection of interpolation method, and the second is the selection of upper limit of interpola-tion time. The common interpolation methods include linear interpolation and polynomial interpolation (curvilinear in-terpolation) and selection should be made based on the variation of the data. The former is suitable for stable and less changed acoustic observation data, whereas the latter is suitable for high dynamic acoustic observation data.

When interpolation is used in lieu of absent observation data, the amount of absent data should be viewed, since not all absences can be supplemented by interpolation. Fig.6a shows the acoustic observation data of the survey line S1T1-S2T1. It is seen from the red circle that data (from about 15 shot points) is absent, indicating that the amount of absent data is on the lower end. Fig.6b shows the results of data in Fig.6a after interpolation processing, indicating that the interpolation can satisfactorily perfect the continuity of the absent data in this shot section. Furthermore, the trend of interpolated data is similar to that of the data before and af-ter, proving that after interpolation, accuracy is guaranteed. Fig.7 shows the acoustic observation data of the survey line S2T11-S1T12. It is seen from the red frame that multiple values (about 250 shot points) are absent with additional ir-regular readings throughout the reading. In this case, too much data is missing and overall continuity is very poor; thus, a large error may occur even if interpolation is con-ducted which would directly affect the positioning accuracy of the acoustic network. Interpolation is not suitable in this case. Such observation values should be eliminated. 3.4.3. Network adjustment report

In the course of network adjustment, adjustment proc-

Fig. 6 Comparison between original acoustic data and interpolated acoustic data


Fig. 7 Observed original acoustic data

essing is conducted to the data of the entire acoustic net-work (via modeling) in order to obtain satisfactory results. The adjusted position of the first acoustic bird behind the near trace is calculated first backwards to the position of next acoustic bird as per the default distance. When errors are discovered between this position and the adjusted acous-tic bird position, this point is returned to the adjusted posi-tion until the end of the cable. Calculation is made forwards to the reference point of the cable from the adjusted position of the first acoustic bird behind the near trace[10].

The network adjustment report intuitively reflects the ef-fect of network adjustment. Table 1 shows the network ad-justment report of a typical survey line. The red data ex-ceeds the set threshold, whereas the black data is within the normal range. It is also observed that the quality of network

adjustment results of the entire survey line is very good, despite of a lack of extensive data. As shown in the table, the data values of S3T15-S2T14 are especially large. Since the observation values of acquired data are sufficient, for the purpose of improving the positioning accuracy, it it suitable to eliminate such large values. However, other red data in the table should not be casually eliminated, which can be determined using the original data. If these are true observa-tions, and the artificial change in preprocessing is low, such a large offset should be retained. If they are the result of er-rors like large values and sharp jumps that are not removed in preprocessing, or there is too much artificial interpolation and extrapolation data in preprocessing, they should be eliminated, so as to ensure accuracy in the positioning of the network.

Table 1 Adjustment of acoustic network

SN Total nodes Rejected nodes Mean Standard deviation Minimum value Maximum value Deviation

S2T7-S2T8 172 0 0.699 0.43767 0.213 1.447 1.660

S2T9-S2T8 172 0 0.657 0.21711 0.215 1.551 1.446

S3T7-S2T8 172 0 0.813 0.27825 0.090 1.864 1.774

S3T9-S2T8 172 2 0.893 0.33248 0.420 1.409 1.829

S1T9-S2T9 172 1 0.537 0.22212 1.299 0.061 1.282

S2T9-S1T9 172 0 0.673 0.43598 0.294 1.549 1.843

S1T9-S2T10 172 5 1.345 0.45220 0.344 3.478 3.135

S1T11-S2T10 172 1 1.425 0.44097 0.525 2.324 1.798

S2T9-S2T10 172 0 0.377 0.27750 0.561 1.090 1.652

S2T11-S2T10 172 0 0.596 0.16159 0.123 1.072 0.949

S3T9-S2T10 172 3 0.250 0.28686 0.949 0.533 1.481

S3T11-S2T10 172 0 0.991 0.40552 0.129 1.791 1.919

S1T11-S2T11 172 0 0.052 0.23137 0.892 0.647 1.539

S2T11-S1T11 172 0 0.097 0.22545 0.824 0.496 1.320

S1T11-S2T12 172 0 0.807 0.22942 0.054 1.475 1.529

S2T11-S2T12 172 0 0.517 0.30229 0.683 1.139 1.822

S3T11-S2T12 172 0 0.428 0.59533 0.550 3.677 4.227

S3T13-S2T12 172 0 0.656 0.29634 0.054 1.539 1.593

S1T15-S2T14 172 2 1.496 0.35816 0.653 2.623 1.971

S2T13-S2T14 172 0 0.830 0.25735 0.205 1.485 1.280

S2T15-S2T14 172 0 0.452 0.29532 1.055 1.300 2.365

S3T13-S2T14 172 0 0.403 0.38104 1.507 0.529 2.099

S3T15-S2T14 172 55 1.182 1.76798 0.681 10.737 11.418

S1T15-S2T15 172 0 0.044 0.28118 0.580 0.748 1.328

S2T15-S1T15 172 0 0.057 0.50582 0.708 2.372 3.080

S1T15-S2T16 172 0 0.630 0.45318 0.812 1.538 2.350

S1T17-S2T16 172 7 2.191 0.82698 0.755 5.841 6.596

S2T15-S2T16 172 0 0.891 0.21554 0.278 1.755 1.477


3.4.4. Variance factors Ordinarily, if the variance factor has a stable change and

low value, it indicates that the adjustment of the survey line is good, and the positioning quality is good. On the other hand, poor positioning quality (see Fig.8) reveals the vari-ance factor comparison of two survey lines. In Fig.8a, the mean and maximum values of variance factors are 0.288 and 0.35 respectively, and the entire survey line changes gently, indicating good performance of the acoustic posi-tioning network. In Fig.8b, the mean of variance factors is 0.348, however, the variance factors start to enlarge from shot point 1796 on (red frame in the figure), and the maxi-mum value reaches 0.53. At this time, the quality of the

acoustic positioning network cannot be evaluated only from the variance factor size and change and the reason for such a phenomenon must be found in the originally acquired acoustic data. When viewed in reverse, the original acoustic observation data, including anomalies in variance factors, show that all data acquired at the cable end of the survey line appears in Fig.9. The acoustic observation data rapidly jumps in value from shot point 1796 (red frame in the fig-ure), prior to verifying the accuracy of the cable’s moving path, thus revealing that the cable end is not straight at this time, resulting poor quality data which in turn negatively affects the variation and size of variance factors and, ulti-mately the accuracy in acoustic network positioning[11].

Fig. 8 Correlation of variance factor variations

4. Conclusions

The acoustic positioning network technique has been widely used in the sea areas of China in recent years and is

becoming a mature method. However, there are few pieces of literature which discuss and analyze the influential fac-tors in the application of the technique. Moreover, there is no definitive criteria for specifying and discriminating the


Fig. 9 Acoustic observation data acquired at the twisted end of the cable

quality of the technique. This paper, for the first time, pre-sents a complete and systematic analysis on the factors in-fluencing the acoustic positioning network of a streamer, and puts forward corresponding innovative methods and op-timization measures that are favorable for reducing the er-rors in offshore acoustic positioning networks, enhancing positioning accuracy, and improving the quality of the seis-mic exploration. In view of the present applications of acoustic positioning networks within China, attention should be paid to the following aspects:

(1) In the acquisition operation of streamer, acquisition status of acoustic data should be monitored in a real-time manner, and the reasons resulting in poor acoustic data ac-quisition quality should be judged. If poor quality results from the factors such as insufficient acoustic bird battery voltage, loss of a retaining ring, coil damage or physical en-trapment, the acoustic bird must be immediately replaced.

(2) Operation in weather with large surges should be avoided. Large surges may affect the acquisition of acoustic data, or unduly influence the cable dynamic variation. Even if high dynamic threshold processing and filtration are adopted, the accuracy of the acoustic positioning network may be compromised.

(3) The quality of an acoustic positioning network cannot be diagnosed through the network adjustment report and the variance factor size alone; it must be diagnosed comprehen-sively, based on the cable state during the operation in addi-tion to the originally acquired data.

(4) It is recommended that post-navigation processing be performed by an experienced engineer or senior operator. In this way, artificial influences can be minimized to achieve optimum positioning accuracy of the acoustic network.

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