Why are some protein sequences known but their 3D structure isn't?
Protein sequencing is a nicely constrained problem: you have a one-dimensional sequence of amino acid members, which come from a limited set of options (made a bit more complicated by post-translational modifications, but not much more so). Because it's one-dimensional, it's a problem you can easily solve by chopping up a protein into little bits, using mass differences between amino acids to understand their constituents, and determining the order from that distribution. If a DNA (or mRNA) sequence is known, it becomes even easier - you can skip the protein sequencing process and get the amino acid sequence directly from the nucleic acid sequence and the genetic code.
By comparison, protein folding is an absolute nightmare to solve for. Chemical bonds between amino acids are not rigid, they can bend and twist in all directions. The conformation of those bonds also depends not just on adjacent amino acids (as in a 1-D problem) but potentially on any other amino acid in the sequence (not to mention external influences..).
In a large molecule like a protein there is a massive massive degrees of freedom problem. From Wikipedia, describing Levinthal's paradox, bold mine:

In 1969, Cyrus Levinthal noted that, because of the very large number of degrees of freedom in an unfolded polypeptide chain, the molecule has an astronomical number of possible conformations. An estimate of 3300 or 10143 was made in one of his papers[1] (often incorrectly cited as the 1968 paper[2]). For example, a polypeptide of 100 residues will have 99 peptide bonds, and therefore 198 different phi and psi bond angles. If each of these bond angles can be in one of three stable conformations, the protein may misfold into a maximum of 3198 different conformations (including any possible folding redundancy). Therefore, if a protein were to attain its correctly folded configuration by sequentially sampling all the possible conformations, it would require a time longer than the age of the universe to arrive at its correct native conformation.

Now, of course that's not the actual process that proteins use to fold (they don't iterate through all possible combinations, they settle through an energy landscape where only certain intermediate conformations are realized), and we can use that in computational models to solve protein structures more quickly than the age of the universe, but it's still quite a slow process. Projects like Folding@home have aimed to distribute the computational load among unused processing power in devices around the world, including idle gaming consoles and personal computers, but there are many many protein structures to solve.
It's possible to get a general picture of protein shape using imaging techniques like X-ray crystallography or cryo-EM, and for some purposes these techniques give a lot of information, but these techniques are also by no means simple and can be prone to errors.