about : processing and gridding gravity data with fatiando a terra

[prince-Ha]

Hello, I know you are very busy, but I am asking you this question because I need your help. After watching the video on YouTube, I am processing the gravitational data with the fatiando tutorial.

1 . there are many differences between simple Bouguer and complete Bouguer , so I ask you what the problem is.

2. run Regional and Residual seperation code, the kernel continue to die.

code : deep_sources.fit((data.easting_m, data.northing_m, data.height_geometric_m), data.gravity_bouguer_mgal)

3. I want to know how to make corrections on the coast and the sea.

I'm worried if it's rude to ask.

Thank you for reading this long article.

I'll attach the file together

thanks

[santisoler]

Hi @prince-Ha! Opening this issue is not rude at all. The idea of allowing users to open issues or discussions in our forum is to encourage the conversation within the community. Your questions and inputs are very welcomed 🙂.

Answer to point 1

After reading your notebook I noticed that your free-air anomaly data doesn't include the observation height. This height is as important as the observed gravity values: the observed gravity depends on the densities of the bodies that generate it and also on the distance to those bodies. In cell 28 you add a height_geometric_m column to your data and you use these values when computing the terrain effect as the observation heights. Those heights are the same as the topographic heights in continental regions and bathymetry depths in oceanic regions. If we assume that the gravity observations where taken through a ground survey, it makes sense to assume that the observation heights will be approximately the topographic height. But I suspect that in the oceanic regions they weren't taken in the deepest point of the sea, but rather at sea level. So the observation heights you choose might be wrong and this might be the source of this difference between the simple Bouguer correction and the terrain effect. I would also recommend you to plot the Bouguer correction along with the terrain effect so you can see their difference easier rather than seeing them directly in the corrected gravities.

Also, take into account that the simple Bouguer correction doesn't depend on observation height because it assumes an infinite plate. This is why simple Bouguer corrections should be taken carefully, while a proper terrain correction is more suitable for most cases.

Answer to point 2

Your kernel is probably crashing due to lack of memory when trying to fit the deep sources. You are working with ~200000 data points and this is no small number for applying equivalent sources.
An alternative would be to use less deep sources: since they are going to be very deep, we don't need too many of them. You can do it by passing a value to the block_size argument of the EquivalentSources. By doing so your region will be divided in blocks of equal size and it will locate a single equivalent source beneath each block. This way you'll end up with less sources than before (when you put one source beneath each data point). Check the EquivalentSources documentation for a complete explanation of this behaviour or the page on Block-averaged equivalent sources in Harmonica's User Guide.

A second alternative would be to use the gradient-boosted equivalent sources: https://www.fatiando.org/harmonica/latest/user_guide/equivalent_sources/gradient-boosted-eqs.html

Answer to point 3

I really regret not including an example on how to correctly apply the correction that that Note mentions. I remember having this example somewhere but don't remember exactly where. @leouieda I think you wrote it, do you think where it can be?

BTW, this more complex example should be included in the Harmonica User Guide! (will open an issue for it)

[santisoler]

Hi @prince-Ha. Thanks for sharing your files. Sorry I didn't have the time to read them thoroughly, but I noticed that you are now defining the height of your observation points in the following cell:

height_sea_level_m = np.where(data.elevation<0, 0, data.elevation)
height_sea_level_m

And using these heights (converted to geometric heights) for the forward modelling step of the terrain effect:

coordinates = (data.easting_m, data.northing_m, data.height_geometric_m)
data = data.assign(terrain_effect_mgal=topography_model.prism_layer.gravity(coordinates, field="g_z"), )

So you're on good track now! Congratulations!

[prince-Ha]

Hi @santisoler

I was the only graduate student in my laboratory, so there was no place to solve my curiosity. But it was nice of you to reply kindly Please help me next time when you have time

Thank you for making a good program.

[santisoler]

Glad to hear that! This is one of the things I love about building communities around the software we develop and use!

[prince-Ha]

Hi, santisoler
1.
I have a question about the Complete Bouguer correction
I used forward modeling for the topographic
https://www.fatiando.org/harmonica/latest/user_guide/topographic_correction.html

I know that the traditional Terrian correction process is the Bullard method(Bullard A, Bullard B, Bullard C)
so, forward modeling for the topographic is the first time I've heard of this method.

• where should I refer the thesis, book, or paper about the modeling correction method
• I used a harmonica code so I want to refer to your code where can I find the reference information
• is it a right doi? (doi: 10.5281/zenodo.3628741)

2. I want to write the SCI thesis but I have no experience... how to prepare it

happy new year thank you

[santisoler]

Hi @prince-Ha!

Blakely (1995, pages 144-145) describes the complete Bouguer correction as approximating the topography with a digital elevation model and forward modelling its gravitational effect on the observation points.

is it a right doi? (doi: 10.5281/zenodo.3628741)

Yes, if you want to cite Harmonica in a scientific article, thesis, etc. that DOI is the one. Check out our Citing Harmonica page in the documentation for more details.

Happy new year for you too!

[kobebryantlin0]

您好，我是林恩伟，你发的邮件我已经收到。