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A velocity inversion refers to the case when seismic velocity decreases, rather than increases, with depth. When this happens, energy refracts away from the normal: This means that no information from the refracting interface returns to the surface, hence no information is gained about that interface, even its very existence. This is demonstrated by the animation below. There are three distinct velocity Layers, but Layer 2 is slower in velocity than Layer 1. The result is a travel time curve that indicates the presence two Layers -- Layers 1 and 3. Layer 2 is not sampled, so there is no evidence of its presence in the record. However, the presence of Layer 2 does impact the travel time plot by moving the crossover distance out farther than it would be otherwise. The result is that not only is Layer 2 not detected, but the depth to Layer 3 is incorrect -- it is calculated to be deeper that it is.

The crossover distance is the distance from the source at which the critically-refracted energy from the next deepest Layer overtakes the critically-refracted energy from the previous Layer (in the two-layer case, the energy traveling through Layer 1 is direct, not refracted energy, but the idea is the same). This is illustrated by the following animation: The direct energy (red) is the first-arrival energy at the first six geophones. However, by the seventh geophone, the direct energy is overtaken by the critically-refracted energy (green). The reciprocal of the slope of each segment is equal to the apparent velocity of the material. If there were a third, even faster Layer, a third slope and second crossover distance would eventually appear on the travel time graph. The crossover distance, along with the velocities indicated by the slopes of the segments, are used to determine the refractor depth.

Hello everyone, my name is Devan, and I would like to open a discussion about finding a lost MagArrow. To give you some background, I lost my MagArrow II while it was mounted below the DJI M400 during a flight mission in a highly dense forest. We have the drone flight log, which indicates that it was stuck in a tree within a 50 m radius of the last known location. We have searched the whole area, but due to a highly dense forest and steep terrain, it was very difficult to find the MagArrow II and the drone on foot. For more than a month, I presume it was still perched within the tree Canopy. And now we have bought a new MagArrow II to continue our survey. In this case, I desperately want to find and retrieve the lost MagArrow using the new device. I have an idea that if I conduct a 5 m spacing grid in both East-West and North-South directions within a 100-meter radius of the last known location, we could eventually narrow down our perimeter by finding an anomaly that indicates the lost device. Therefore, I have a few questions:1. How magnetic is the drone and the MagArrow II?2. Is it feasible to find the old MagArrow with the new MagArrow with the stated method? Alternatively, do you have any effective suggestions for a different approach? I appreciate any insights you can provide. Thank you!

Channel Remapping Channel remapping allows you to change: the order of channels on each analog spread cable that connects to the Geode reorder the Geode boxes. You would use this option if your cables were wired opposite to the default order normally used in Geometrics wiring, if you wished to turn your line around to have the low channels at the opposite end, or if your cables had a wiring error. Channel remapping is also often necessary when using more that a Single network cable. Default cable wiring of Geometrics seismographs Default order is defined as the natural electrical order in which channels are oriented when the system first powers up before remapping. Refer to Section 3 under Connector Wiring that discusses standard wiring configurations. You may have requested a custom wiring configuration from Geometrics. If you are confused about your wiring, contact the factory and refer to the serial number and job number. Geode cables are typically wired in a ‘high-side configuration’, meaning that the Geode connects closest to the highest numbered channel on the analog cable. The 149 figure above shows this configuration for a Single box system, with 24 channels. Multiple Geodes The following diagram shows a default Single digital line (one network card) system with 3 Geodes. Note that Geode one is always closest to the controller in a default configuration. Multiple Network Lines The next diagram below shows a default configuration with two digital lines (two network cards) with the controller positioned in the middle. Line 1 is on the left and line 2 is on the right. One might use two lines to increase data throughput to reduce time between shots. Like the configuration above, the Geodes are numbered starting closest to the controller. The seismic controller software labels all of the channels contiguously even though they are on two separate digital lines. However, if the lines are collinear, the first line will have the channels ordered backwards. This can be easily rectified with the remapping feature. There are two ways of remapping channels: automatic mode and manual mode. Automatic mode settings are listed on the top of the remapping dialog box, and manual mode on the bottom. Automatic Channel Remapping Automatic channel remapping allows you to reverse either the order of the Geodes on the line, or reverse the order of the channels on the spread cable. The above diagram shows the result after both channels and Geodes have been reversed, renumbering the line so that low channels start on the left hand side and increase towards the right. In the dialog box, the automatic remapping boxes referencing line 2 remain unchecked, since the default orientation on line two was correct. Manual Channel Remapping Channels can be remapped on an individual basis using the Manual Map Mode. Select the appropriate check box, and enter the order in which you would like the channels that differs from the default order. You can specify individual channels separated by a comma (1, 3, 4, 6 etc) or a range of channels (1-13, 24-14 etc). For example, if you wanted the channels ordered backwards on a 24-channel system, you would enter 24-1. If you wished to reverse the order of channels 1- 12 in a 24 channel system, you would type 12-1, 13-24. Other examples are shown opposite, and are available by pressing the See Examples button on the remapping menu.

Color representationRed: data collected by a survey magnetometer, such as a MagArrowGreen: survey data we are interested inBlue: base-station data Magnetic field is a function of location (r) and time (t): B(r,t)In general, we are only interested in magnetic field as a function of location: B(r). Ideally, we set up one magnetometer at each location of interest and measure the magnetic field at different locations at the same time. This method removes the time dependence.However, the method requires many magnetometers. The common practice is to move one magnetometer around. In this case, B(r,t) is collected since it takes time to move the magnetometer. To remove the time dependence, a base-station is required. Assume the base-station reading at a fixed location R1 is B1(R1,t) = c1 + B1(t), where c1 is a constant, depending on R1. We hope to achieve the base-station correction B(r,t) - B1(R1,t) = B(r) – c1.For a Single base-station location, c1 can be ignored since it is a constant offset applied to the whole survey area. In another word, B(r) and B(r) – c1 generate the same survey color map. For large scale surveys, it is impossible to have a Single base-station location, since it is not economical and magnetic field time dependence is also regional.Now we obtain base-station data sets at different locations: B1(R1,t), B2(R2,t), B3(R3,t)… When the base-station correction is applied, Bi(r,t) - Bi(Ri,t) = Bi(r) – ci. In general, ci are different. Therefore, Bi(r,t) - Bi(Ri,t) can NOT be combined directly into a Single data base unless constant offsets are applied to achieve Bi(r). A typical combined 5-day survey without applying offsets is shown below. These constant offsets are hard to measure, unless multi base-stations are set up. However, they can be calculated based on the overlapping areas between two data sets since the readings in the overlapping areas must be the same, assuming the same AGL (above ground level). With this method, the new combined data is shown below. Geometrics offers an auto survey combination program for MagArrow and MagEx customers. Attachment : Survey_Data_Stitch_Auto_V3.zip

You can transfer your SeisImager license from one computer to another using the following guide. SeisImager has a function to erase velocity model where ray path did not propagate. It is not automatic. Select "Velocity model", ""Define bottom Layer", "Manually". Then click the mouse from left to right to define a line to truncate velocity model as shown below. Final Result:

Every second, the NMEA strings, delimited by Single quotation marks, are included as separate columns. The strings also contains commas. Therefore, there will be more columns if you use comma as the only delimiter. The correct import setting should be comma-separated, with Single quotation marks as string delimiters. All of those "extra" columns will be revealed as the original RMC and GGA NMEA strings.

Dead-Zones The MagArrow is a dual sensor magnetometer powered by MFAM sensors, but it is configured for use so it only has a Single data output. The reason Geometrics has done this is so we could ensure the MagArrow encounters no "dead-zones". A dead-zone occurs when the orientation of a magnetometer results in the magnetometer producing poor or no measurements. The dead-zone angle depends on the location of survey. Since we have the two MagArrow MFAM sensors in orthogonal orientations, the MagArrow Magnetometer has operability worldwide without affecting survey orientation, making it much easier to use for the customer. Heading Errors Heading errors are a type of noise magnetometers can experience. They come from three sources: Sensor Console Operator Magnetic materials in the sensor itself are the primary cause of heading errors. The physics of Cesium and Potassium magnetometers can contribute small amounts to the total heading error. Magnetic contamination near the sensors, operating electronics, or operator can all contribute to heading error. Heading errors look like herringbone patterns in survey images. Alternate lines can also be corrugated. Dead-Zones vs Heading Errors while these two sources of error in magnetic data are different, there is overlap between them when operating a magnetometer like the MagArrow. Heading errors can be fixed relatively easily in software, where dead zones can be much harder to manage. If a line is completely ruined because of a dead zone then they will need to re-fly the line/mission which is time consuming. Even with advanced users, these sorts of mishaps can happen. Additionally, the closer a mag sensor operates to a dead-zone, the larger a heading error will be measured. With compensation software and a pre-survey heading error flight, heading error can be reduced dramatically to around 1 nT for the MagArrow. Click to view the difference between Raw and Processed MagArrow Data The MagArrow is only outputting a Single value as a means to create a “no-dead-zone” system. Obviously each sensor has a dead zone themselves, but with the sensors orientated orthogonally at least one sensor at all times will have a magnetic measurement. By combining the measurements from both sensors it is possible to generate a constant magnetic field measurement independent of orientation and location in the world. If the data from each MFAM sensor in the MagArrow was individually reported there would be gaps in the mag fields observed by either sensor as you fly, rotate, and swing.

Raw Data MagArrow data is imported into Survey Manager in the form of .MAGDATA files, downloaded from the MagArrow. The .MAGDATA file contains measurements from different sensors inside the MagArrow: 1000Hz magnetometer readings; accelerometer, gyro, compass, temperature readings; and GPS info. MFAM assigns a fiducial number, or “FID” to each magnetometer reading, in a cycle from 1 to 1000 that repeats every second. In the instrument, the magnetometer readings and the GPS sentence data are synchronized so that the “FID-1” magnetometer record is matched with the GPS location and timing information. Exports to CSV and Geosoft file formats 1000Hz un-filtered export The 1000Hz export provides the original raw magnetometer data plus some simple interpolations: • Magnetometer reading: The raw magnetic field values are exported without application of a filter. [While these raw measurements are the output of a filter inside the MFAM sensor: a 9-pole Butterworth low pass filter with a -3dB point at 400Hz, that filter is considered part of the sensor for this description.] • Auxiliary sensors: Gyro, accelerometer, and temperature are acquired once per every 5 magnetometer readings, and are reported only when acquired. Compass readings are acquired one per every 10 magnetometer readings and are reported only when acquired. • GPS NMEA sentence: Reported with the associated FID-1 mag record. A few individual fields from the GPS are also broken out from the GPS sentence and reported separately, without interpolation. • Interpolated GPS fields: Time, date, latitude, longitude, and track (course over ground) are linearly interpolated between GPS readings. Decimated exports Each of the exports at frequencies from 10 Hz to 100 Hz is a decimation – data are filtered by a low-pass filter and then down-sampled to the target sample rate. Each low-pass filter (a different one for each decimation) is a symmetric finite impulse response (or FIR) filter, with the following design goals: • -3dB attenuation at 0.75 * Nyquist frequency (e.g., the -3dB point for the 10Hz decimation is 3.75Hz) • Significant attenuation of 50Hz and 60Hz signals. • Reasonably flat response in the pass band. Linear phase (or zero phase, or constant group delay) filters. These filters are not Kalman filters. The filters are applied to fields in the decimations as follows: • Magnetometer readings: Magnetometer readings are decimated: the FIR is applied, then the data are down-sampled to the target rate. • Aux sensors: Aux sensors are first up-sampled to 1000Hz by linear interpolation of values between individual readings (which occur once every 5 mag readings for gyro, accelerometer, and temperature, and once every 10 mag readings for compass). Then these 1000Hz values are decimated in the same process as the magnetometer readings. • Latitude and longitude are first up-sampled to 1000Hz by linear interpolation of values between successive GPS data (once per second), then these 1000 Hz values are decimated in the same process as the magnetometer readings. • Time, date, and track are linearly interpolated as in the raw, unfiltered 1000Hz export. Merging filtered and unfiltered data. Some of the values in an individual line of data are filtered: mag readings, aux sensors, etc. Other measurements are not filtered: time and date, GPS sentences, record counters, and the simple interpolated fields. These two sets of values – filtered and unfiltered, must be reported in individual lines that contain values of both types. The question “How should the two sets of values be matched?” is addressed as follows: A decimation filter has a center. For example, a Single filter result that weighs 499 individual measurements running from record number 752 to record number 1250 (in DSP terms, it is the result of the convolution of 499 input values with 499 filter weights), is centered on record number 1001. The result is the “filtered value of record 1001”. In a Single line along with this value should be the other filtered results centered on record number 1001 plus the unfiltered raw and interpolated values that were recorded as part of the original, raw record 1001. The down-sampling part of decimation involves keeping some results and discarding others; down-sampling from 1000Hz to 100Hz includes discarding 9 out of 10 results. During exports, Survey Manager keeps the “FID 1” record, because it includes the original GPS information, then discards the next 9 records (if it’s a 100Hz decimation), and then repeats the pattern, each time starting with FID 1. If you have questions about the MagArrow decimations, please contact your Geometrics account manager.

A common question many have with magnetic surveys is "How wide of a survey swath does a Single magnetometer sensor cover on a Single pass?" The answer is it depends on what is being searched for. Magnetometers are passive instruments, meaning they don’t actively send out signals or have a limited swath or depth of exploration. When planning a magnetic survey the grid (line spacing and waypoint spacing) should be designed using the best possible model of the target. There are some general rules of thumb that can be used to determine typical detection ranges for common iron objects. For example, a 10lb sledgehammer has been lost and needs to be found, and assuming this is 10lbs of pure iron, it would be expected to see a 1nT anomaly when the magnetometer sensor passes 6 meters over the top of the tool. Knowing this, survey line spacings should not be any narrower than 6 meters. With a line spacing of 3 meters, the chances of getting a clear anomaly goes up 8 fold as the 10lb iron sledgehammer would be at a minimum a 8nT anomaly vs a 1nT anomaly. In a geological sense, let's say we have a mafic dike intrusion that we believe is running E-W and it extends at least 25 meters in the near-surface in a somewhat linear fashion. It's difficult to model the amount of iron in a geological structure like this, so the survey should be designed to cross the dike perpendicularly every 5 meters or so, making sure to cross over the dike several times. Each pass over the dike may exhibit an anomaly of similar amplitude, and the feature will show up as a clear linear feature in the final processed map. For general mapping of geology, you have a lot of options. Most commonly mineral exploration surveys are done over very large areas, so the line spacing is wider to save time as the lower resolution model that results still accomplishes the task of finding large mineral deposits. If more detail is required, then a more fine-grained survey can be done later. 20m-50m line spacing is typical for mineral exploration surveys. Design a survey grid to completely encompass the area of interest (i.e. make sure you get some data outside of the areas of interest, in case an interesting anomaly lies right along the edge). The founder of Geometrics the late Sheldon Breiner called this the Law of Search, as he often found his targets of interest along the edges of his archaeological magnetic surveys. It is important to make sure the operator of the magnetometer is magnetically clean before surveying with the magnetometer. This means no steel toe boots, glasses or hats with metal fittings, cellphone, belt buckle, etc. Magnetometer data acquisition is fairly simple, but data interpretation can be complex. You may need a base-station too. Please refer to the Base-Station information.

If you're exporting data from G-864, MagArrow, or MagEx, using any of the export tools - Quick Conversion, Command-line conversion, or export from a project and survey in Survey Manager - and you don't get any data, or you think the export is missing some data, follow these steps: Verify that you have records to export: In survey manager, verify that the survey has data in it: there's a "Measurements" field in the survey details. For MagArrow, if you're using Quick Conversion or the command line program, you will need to create a project and survey in Survey Manager and import the .magdata file into it. If you don't have any data records, then verify that you've opened the correct file. If you have records, but they just don't seem to be exporting, then choose to export invalid records and records without locations The export functions in Survey Manager allow you to choose this option with the "Filter" choices: Look in the exported file for records without locations (no GPS) and with invalid records; they are not included in the default exports. For MagArrow, export with 1000 samples/second. If you are troubleshooting an export at a decimated rate (e.g. 20 samples/second) then note that a Single invalid record in the 1000 samples/second original data may invalidate about 1/2 second of data; in a 20 samples/second MagArrow decimation, a Single 1000 samples/second invalid record will invalidate about 10 decimated results.

Hey There is no hardware limitation to use UART4 or UART5 for your application. The previous post you read was talking about UART not being implemented in the example code and not specifically about UART5. The existing pipeline does assume a Single consumer and you will run into race conditions if you only implement a mailbox_pend for your UART transmission. I would recommend that you either remove the TCP mailbox or create a new mailbox for UART. We have tried UART streaming before without issue. Transmitting the raw binary data will cause issues with some receiver implementations as the values 0x00(NULL char in ASCII), 0x0A or 0x0D which usually denote the end of a serial transmission occur regularly in the MFAM data. Two options to avoid this issue:1. Convert the fields you are interested in to ASCII before sending them over UART.2. Send a fixed number of bytes and implement binary mode on your receiver and request the same number of bytes. One other issue to watch out for in binary mode is if the receiver starts receiving data in the middle of a transmission the transmitter and receiver will be out of sync. There are two handshake signal lines available on the UART4 port on the DevKit called RTS and CTS(Request to Send and Clear to Send). You can use these lines to synchronize the transmitter and receiver. There are software options available as well to implement this synchronization. Hope this helps.

Hello, I saw in a previous post that the current firmware only supports MFAM streaming via Ethernet, and that UART5 isn't supported. I'm modifying the Dev Kit firmware to add TX output on UART4 instead, by adding a parallel Mailbox_post in spiTaskFxns.c to a new UART4 TX task/mailbox, at 460800 bps. Before going further, I wanted to ask: Is there any hardware-level reason UART4 wouldn't work here, beyond it just not being implemented in the stock firmware? Does the existing SPI→Ethernet pipeline assume a Single consumer, in a way that could cause timing issues if I add a second parallel mailbox post for UART4? Has anyone tried UART-based streaming from the Dev Kit before, and if so, any known pitfalls? Thanks in advance!

Hello, I wanted to try our MagEditor software, but it didn't accept any of the files I converted to 10 Hz, 20 Hz, 50 Hz, 100 Hz, and 1000 Hz CSV formats from Survey Manager. What's the reason and how can I fix it? My operating system is Windows 11 Home Single, and my computer specifications are:Processor: Intel(R) Core(TM) i9-14900HX (2.20 GHz)Installed RAM: 32.0 GB (usable: 31.6 GB)System type: 64-bit operating system, x64-based processor.

The answer is NO. MagArrow or MagEx operate in the so-called combined sensor mode. The Single reading is NOT the averaged reading from the 2 sensors inside. Instead, the signals from the 2 sensors are combined and then data processed to produce one reading. To us, there is no point to produce 2 readings if 2 sensors are right next to each other. We are open to discussions!