diff --git a/.gitignore b/.gitignore
index 29cf53ef64723c8b6822c87dc308132d623475bf..783a7aa28f771cc42ba8cc5cee2609bede24c08f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -10,4 +10,6 @@ dist
 
 tests/resources/test_output
 
-pydoubletcalc_install
\ No newline at end of file
+pydoubletcalc_install
+
+workdir
\ No newline at end of file
diff --git a/pixi.lock b/pixi.lock
index e0f720c2709a21cbfcbcf64c7cbe2b2cc8018d4d..b8901cf9ba2b0f8305d9b33472d52ea4357c5bb7 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -52,9 +52,11 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/dask-2025.5.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/dask-core-2025.5.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/dbus-1.13.6-h5008d03_3.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/noarch/deprecated-1.3.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/distlib-0.4.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/distributed-2025.5.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/docutils-0.21.2-pyhd8ed1ab_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/donfig-0.8.1.post1-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/et_xmlfile-2.0.0-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/exceptiongroup-1.3.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/expat-2.7.0-h5888daf_0.conda
@@ -63,6 +65,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/gflags-2.2.2-h5888daf_1005.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/ghp-import-2.1.0-pyhd8ed1ab_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/glog-0.7.1-hbabe93e_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/google-crc32c-1.7.1-py313h74173ec_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/griffe-1.7.3-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/h2-4.2.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/hpack-4.1.0-pyhd8ed1ab_0.conda
@@ -164,6 +167,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/nlohmann_json-3.12.0-h3f2d84a_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/nodeenv-1.9.1-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/numba-0.62.1-py313hd8e3f9f_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/numcodecs-0.16.5-py313h08cd8bf_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/numpy-2.2.5-py313h17eae1a_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/openjpeg-2.5.3-h5fbd93e_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/openpyxl-3.1.5-py313h9c9eb82_1.conda
@@ -231,11 +235,13 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/virtualenv-20.34.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/watchdog-6.0.0-py313h78bf25f_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/wheel-0.45.1-pyhd8ed1ab_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/xarray-2024.9.0-pyhd8ed1ab_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/wrapt-1.17.3-py313h07c4f96_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/xarray-2025.12.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxau-1.0.12-hb9d3cd8_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxdmcp-1.1.5-hb9d3cd8_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/xyzservices-2025.4.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/yaml-0.2.5-h7f98852_2.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/noarch/zarr-3.1.5-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/zict-3.0.0-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/zipp-3.21.0-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/zlib-1.3.1-hb9d3cd8_2.conda
@@ -306,14 +312,17 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/noarch/dask-2025.5.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/dask-core-2025.5.1-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/deprecated-1.3.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/distlib-0.4.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/distributed-2025.5.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/docutils-0.21.2-pyhd8ed1ab_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/donfig-0.8.1.post1-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/et_xmlfile-2.0.0-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/exceptiongroup-1.3.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/filelock-3.19.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/fsspec-2025.5.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/ghp-import-2.1.0-pyhd8ed1ab_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/win-64/google-crc32c-1.7.1-py313h5327936_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/griffe-1.7.3-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/h2-4.2.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/hpack-4.1.0-pyhd8ed1ab_0.conda
@@ -400,6 +409,7 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/noarch/nodeenv-1.9.1-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/win-64/numba-0.62.1-py313h924e429_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/win-64/numcodecs-0.16.5-py313hc90dcd4_0.conda
       - conda: https://conda.anaconda.org/conda-forge/win-64/numpy-2.2.5-py313hefb8edb_0.conda
       - conda: https://conda.anaconda.org/conda-forge/win-64/openjpeg-2.5.3-h4d64b90_0.conda
       - conda: https://conda.anaconda.org/conda-forge/win-64/openpyxl-3.1.5-py313he57e174_1.conda
@@ -470,11 +480,13 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/noarch/wheel-0.45.1-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/win_inet_pton-1.1.0-pyh7428d3b_8.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/xarray-2024.9.0-pyhd8ed1ab_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/win-64/wrapt-1.17.3-py313h5ea7bf4_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/xarray-2025.12.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/win-64/xorg-libxau-1.0.12-h0e40799_0.conda
       - conda: https://conda.anaconda.org/conda-forge/win-64/xorg-libxdmcp-1.1.5-h0e40799_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/xyzservices-2025.4.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/win-64/yaml-0.2.5-h8ffe710_2.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/noarch/zarr-3.1.5-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/zict-3.0.0-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/zipp-3.21.0-pyhd8ed1ab_1.conda
       - conda: https://conda.anaconda.org/conda-forge/win-64/zstandard-0.23.0-py313ha7868ed_2.conda
@@ -1624,6 +1636,18 @@ packages:
   purls: []
   size: 618596
   timestamp: 1640112124844
+- conda: https://conda.anaconda.org/conda-forge/noarch/deprecated-1.3.1-pyhd8ed1ab_0.conda
+  sha256: c994a70449d548dd388768090c71c1da81e1e128a281547ab9022908d46878c5
+  md5: bf74a83f7a0f2a21b5d709997402cac4
+  depends:
+  - python >=3.10
+  - wrapt <2,>=1.10
+  license: MIT
+  license_family: MIT
+  purls:
+  - pkg:pypi/deprecated?source=hash-mapping
+  size: 15815
+  timestamp: 1761813872696
 - conda: https://conda.anaconda.org/conda-forge/noarch/distlib-0.4.0-pyhd8ed1ab_0.conda
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   md5: 003b8ba0a94e2f1e117d0bd46aebc901
@@ -1674,6 +1698,18 @@ packages:
   - pkg:pypi/docutils?source=hash-mapping
   size: 402700
   timestamp: 1733217860944
+- conda: https://conda.anaconda.org/conda-forge/noarch/donfig-0.8.1.post1-pyhd8ed1ab_1.conda
+  sha256: d58e97d418f71703e822c422af5b9c431e3621a0ecdc8b0334c1ca33e076dfe7
+  md5: c56a7fa5597ad78b62e1f5d21f7f8b8f
+  depends:
+  - python >=3.9
+  - pyyaml
+  license: MIT
+  license_family: MIT
+  purls:
+  - pkg:pypi/donfig?source=hash-mapping
+  size: 22491
+  timestamp: 1734368817583
 - conda: https://conda.anaconda.org/conda-forge/noarch/et_xmlfile-2.0.0-pyhd8ed1ab_1.conda
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   md5: 71bf9646cbfabf3022c8da4b6b4da737
@@ -1864,6 +1900,37 @@ packages:
   purls: []
   size: 143452
   timestamp: 1718284177264
+- conda: https://conda.anaconda.org/conda-forge/linux-64/google-crc32c-1.7.1-py313h74173ec_1.conda
+  sha256: 81ca7fb5c0756e3a5934fe18b44b90be475a03329bcd715334455aec340e34c0
+  md5: 8580f244242b4d6a8c1933d8d0475b9c
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+  - libcrc32c >=1.1.2,<1.2.0a0
+  - libgcc >=14
+  - python >=3.13,<3.14.0a0
+  - python_abi 3.13.* *_cp313
+  license: Apache-2.0
+  license_family: Apache
+  purls:
+  - pkg:pypi/google-crc32c?source=hash-mapping
+  size: 24798
+  timestamp: 1755850411927
+- conda: https://conda.anaconda.org/conda-forge/win-64/google-crc32c-1.7.1-py313h5327936_1.conda
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+  md5: 35b1131e4ea5eb0f27664eeb68c9a29b
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+  - python >=3.13,<3.14.0a0
+  - python_abi 3.13.* *_cp313
+  - ucrt >=10.0.20348.0
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  license: Apache-2.0
+  license_family: Apache
+  purls:
+  - pkg:pypi/google-crc32c?source=hash-mapping
+  size: 27799
+  timestamp: 1755850484807
 - conda: https://conda.anaconda.org/conda-forge/noarch/griffe-1.7.3-pyhd8ed1ab_0.conda
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@@ -4178,6 +4245,46 @@ packages:
   - pkg:pypi/numba?source=hash-mapping
   size: 5706597
   timestamp: 1759165298367
+- conda: https://conda.anaconda.org/conda-forge/linux-64/numcodecs-0.16.5-py313h08cd8bf_0.conda
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+  md5: 0f394ef25fb81d1dec8ff4fa716f00bd
+  depends:
+  - __glibc >=2.17,<3.0.a0
+  - deprecated
+  - libgcc >=14
+  - libstdcxx >=14
+  - msgpack-python
+  - numpy >=1.23,<3
+  - numpy >=1.24
+  - python >=3.13,<3.14.0a0
+  - python_abi 3.13.* *_cp313
+  - typing_extensions
+  license: MIT
+  license_family: MIT
+  purls:
+  - pkg:pypi/numcodecs?source=hash-mapping
+  size: 808201
+  timestamp: 1764782369322
+- conda: https://conda.anaconda.org/conda-forge/win-64/numcodecs-0.16.5-py313hc90dcd4_0.conda
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+  md5: 4006d795b35200d0d6e28a1de84dfcc5
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+  - msgpack-python
+  - numpy >=1.23,<3
+  - numpy >=1.24
+  - python >=3.13,<3.14.0a0
+  - python_abi 3.13.* *_cp313
+  - typing_extensions
+  - ucrt >=10.0.20348.0
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  license: MIT
+  license_family: MIT
+  purls:
+  - pkg:pypi/numcodecs?source=hash-mapping
+  size: 516677
+  timestamp: 1764782612807
 - conda: https://conda.anaconda.org/conda-forge/linux-64/numpy-2.2.5-py313h17eae1a_0.conda
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@@ -4945,10 +5052,10 @@ packages:
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   name: pythermogis
   version: 1.2.0
-  sha256: 35de67af8136fb6442b90f5a2956e6ac57f8a6f52f1fbbfad15768e83e08b31f
+  sha256: 5307b5b9e674861991952ee2bb4da21dfc517e11259fd4ed7735f28b5fb54408
   requires_dist:
   - jpype1>=1.5.2,<2
-  - xarray==2024.9.0.*
+  - xarray==2025.12.0.*
   - pandas>=2.2.3,<3
   - pytz>=2024.1,<2025
   - build>=1.2.2.post1,<2
@@ -5949,41 +6056,73 @@ packages:
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   size: 9555
   timestamp: 1733130678956
-- conda: https://conda.anaconda.org/conda-forge/noarch/xarray-2024.9.0-pyhd8ed1ab_1.conda
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-  md5: dc790d427d89b85ae12fc094e264833f
+- conda: https://conda.anaconda.org/conda-forge/linux-64/wrapt-1.17.3-py313h07c4f96_1.conda
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   depends:
-  - numpy >=1.24
-  - packaging >=23.1
-  - pandas >=2.1
-  - python >=3.10
+  - __glibc >=2.17,<3.0.a0
+  - libgcc >=14
+  - python >=3.13,<3.14.0a0
+  - python_abi 3.13.* *_cp313
+  license: BSD-2-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/wrapt?source=hash-mapping
+  size: 64865
+  timestamp: 1756851811052
+- conda: https://conda.anaconda.org/conda-forge/win-64/wrapt-1.17.3-py313h5ea7bf4_1.conda
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+  md5: 3e199c8db04833fe628867462aeaca24
+  depends:
+  - python >=3.13,<3.14.0a0
+  - python_abi 3.13.* *_cp313
+  - ucrt >=10.0.20348.0
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  license: BSD-2-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/wrapt?source=hash-mapping
+  size: 63385
+  timestamp: 1756851987645
+- conda: https://conda.anaconda.org/conda-forge/noarch/xarray-2025.12.0-pyhcf101f3_0.conda
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+  md5: efdb3ef0ff549959650ef070ba2c52d2
+  depends:
+  - python >=3.11
+  - numpy >=1.26
+  - packaging >=24.1
+  - pandas >=2.2
+  - python
   constrains:
-  - seaborn-base >=0.12
-  - distributed >=2023.9
-  - scipy >=1.11
+  - bottleneck >=1.4
+  - cartopy >=0.23
+  - cftime >=1.6
+  - dask-core >=2024.6
+  - distributed >=2024.6
+  - flox >=0.9
+  - h5netcdf >=1.3
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+  - hdf5 >=1.14
+  - iris >=3.9
+  - matplotlib-base >=3.8
+  - nc-time-axis >=1.4
   - netcdf4 >=1.6.0
+  - numba >=0.60
+  - numbagg >=0.8
+  - pint >=0.24
+  - pydap >=3.5.0
+  - scipy >=1.13
+  - seaborn-base >=0.13
+  - sparse >=0.15
   - toolz >=0.12
-  - nc-time-axis >=1.4
-  - cftime >=1.6
-  - h5netcdf >=1.2
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-  - h5py >=3.8
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-  - hdf5 >=1.12
-  - numba >=0.57
-  - iris >=3.7
-  - cartopy >=0.22
-  - dask-core >=2023.9
-  - flox >=0.7
-  - bottleneck >=1.3
-  - pint >=0.22
-  - sparse >=0.14
+  - zarr >=2.18
   license: Apache-2.0
   license_family: APACHE
   purls:
   - pkg:pypi/xarray?source=hash-mapping
-  size: 801066
-  timestamp: 1728453306227
+  size: 994025
+  timestamp: 1764974555156
 - conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxau-1.0.12-hb9d3cd8_0.conda
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   md5: f6ebe2cb3f82ba6c057dde5d9debe4f7
@@ -6062,6 +6201,27 @@ packages:
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   size: 63274
   timestamp: 1641347623319
+- conda: https://conda.anaconda.org/conda-forge/noarch/zarr-3.1.5-pyhcf101f3_0.conda
+  sha256: c36bec7d02d2f227409fcc4cf586cf3a658af068b58374de7f8f2d0b5c1c84f9
+  md5: c1844a94b2be61bb03bbb71574a0abfc
+  depends:
+  - python >=3.11
+  - packaging >=22.0
+  - numpy >=1.26
+  - numcodecs >=0.14
+  - typing_extensions >=4.9
+  - donfig >=0.8
+  - google-crc32c >=1.5
+  - python
+  constrains:
+  - fsspec >=2023.10.0
+  - obstore >=0.5.1
+  license: MIT
+  license_family: MIT
+  purls:
+  - pkg:pypi/zarr?source=hash-mapping
+  size: 305998
+  timestamp: 1763742695201
 - conda: https://conda.anaconda.org/conda-forge/noarch/zict-3.0.0-pyhd8ed1ab_1.conda
   sha256: 5488542dceeb9f2874e726646548ecc5608060934d6f9ceaa7c6a48c61f9cc8d
   md5: e52c2ef711ccf31bb7f70ca87d144b9e
diff --git a/pyproject.toml b/pyproject.toml
index b0c22a3131b0acb86fdaf281056289941822f0c8..e418f04ff01ac1f51b1abb5c55780621e40827c2 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -16,7 +16,7 @@ license = { file = "LICENSE" }
 requires-python = ">=3.11"
 dependencies = [
     "jpype1>=1.5.2,<2",
-    "xarray==2024.9.0.*",
+    "xarray==2025.12.0.*",
     "pandas>=2.2.3,<3",
     "pytz>=2024.1,<2025",
     "build>=1.2.2.post1,<2",
@@ -42,6 +42,7 @@ platforms = ["win-64", "linux-64"]
 
 [tool.pixi.pypi-dependencies]
 pythermogis = { path = ".", editable = true }
+#pydoubletcalc = { path = 'C:\Users\knappersfy\work\thermogis\pydoubletcalc', editable = true }
 
 [tool.pixi.tasks]
 test = "PYTHONPATH=src/pythermogis pytest -s tests/"
@@ -53,7 +54,7 @@ pytg = "PYTHONPATH=src pixi run python src/pythermogis/main.py"
 [tool.pixi.dependencies]
 python = ">=3.13.2,<3.14"
 jpype1 = ">=1.5.2,<2"
-xarray = "2024.9.0.*"
+xarray = "2025.12.0.*"
 pandas = ">=2.2.3,<3"
 setuptools = ">=75.8.2,<76"
 wheel = ">=0.45.1,<0.46"
@@ -71,6 +72,7 @@ pre-commit = ">=4.3.0,<5"
 python-dotenv = ">=1.2.1,<2"
 numba = ">=0.62.1,<0.63"
 ruff = ">=0.14.8,<0.15"
+zarr = ">=3.1.5,<4"
 
 [tool.ruff]
 line-length = 88
diff --git a/src/pythermogis/thermogis_classes/doublet.py b/src/pythermogis/thermogis_classes/doublet.py
index 50d31633c4abef871eecaac9fed89b9e0e2ed200..b802ca15b9ed516bdd25491967f1cd0f68800773 100644
--- a/src/pythermogis/thermogis_classes/doublet.py
+++ b/src/pythermogis/thermogis_classes/doublet.py
@@ -2,7 +2,7 @@ import numpy as np
 import xarray as xr
 from jpype import JClass
 from pythermogis.workflow.utc.doublet import calculate_doublet_performance, DoubletInput, DoubletOutput
-from pythermogis.workflow.utc.utc_properties import UTCConfiguration
+from pythermogis.workflow.utc.configuration import UTCConfiguration
 
 
 def simulate_doublet(
diff --git a/src/pythermogis/transmissivity/calculate_thick_perm_trans.py b/src/pythermogis/transmissivity/calculate_thick_perm_trans.py
index aa485e7c230112f5b9149ef0388e66f43fdd6025..05a65b7ed7cc12e575df0f0c041881e3ac0bb658 100644
--- a/src/pythermogis/transmissivity/calculate_thick_perm_trans.py
+++ b/src/pythermogis/transmissivity/calculate_thick_perm_trans.py
@@ -1,6 +1,9 @@
 import numpy as np
 from scipy import stats
 import xarray as xr
+from numba import njit, prange
+from numpy.typing import NDArray
+
 
 def generate_thickness_permeability_transmissivity_for_pvalues(thickness_mean: float, thickness_sd: float, ln_permeability_mean: float, ln_permeability_sd: float, p_values: xr.DataArray, nSamples: int = 10000) -> float:
     """
@@ -52,4 +55,66 @@ def generate_thickness_permeability_transmissivity_for_pvalues(thickness_mean: f
     sample_indexes = np.array(p_value_fractions * nSamples)
     transmissivity_pvalues_sampled = transmissivity_samples[sample_indexes.astype(int)]
 
-    return thickness_pvalues, permeability_pvalues, transmissivity_pvalues_sampled
\ No newline at end of file
+    return thickness_pvalues, permeability_pvalues, transmissivity_pvalues_sampled
+
+
+@njit(parallel=True)
+def calculate_transmissivity(
+        thickness_mean: NDArray[np.float64],
+        thickness_sd: NDArray[np.float64],
+        ln_perm_mean: NDArray[np.float64],
+        ln_perm_sd: NDArray[np.float64],
+        quantile: float,
+        z_score: float,
+        n_samples: int,
+):
+    shape = thickness_mean.shape
+    tm_flat = thickness_mean.ravel()
+    ts_flat = thickness_sd.ravel()
+    lpm_flat = ln_perm_mean.ravel()
+    lps_flat = ln_perm_sd.ravel()
+
+    n_cells = tm_flat.size
+    idx = int(quantile * n_samples)
+
+    thickness_p = np.empty(n_cells)
+    permeability_p = np.empty(n_cells)
+    transmissivity_p = np.empty(n_cells)
+
+    for i in prange(n_cells):
+        tm = tm_flat[i]
+        ts = ts_flat[i]
+        lpm = lpm_flat[i]
+        lps = lps_flat[i]
+
+        if np.isnan(tm) or np.isnan(ts) or np.isnan(lpm) or np.isnan(lps):
+            thickness_p[i] = np.nan
+            permeability_p[i] = np.nan
+            transmissivity_p[i] = np.nan
+            continue
+
+        # Generate samples for this cell
+        thickness_samples = np.empty(n_samples)
+        ln_perm_samples = np.empty(n_samples)
+
+        for j in range(n_samples):
+            if ts == 0:
+                thickness_samples[j] = tm
+            else:
+                thickness_samples[j] = max(0.01, np.random.normal(tm, ts))
+            ln_perm_samples[j] = np.random.normal(lpm, lps)
+
+        # Transmissivity samples
+        tr_samples = np.exp(ln_perm_samples) * thickness_samples
+        tr_samples.sort()
+        transmissivity_p[i] = tr_samples[idx]
+
+        # Analytical percentiles
+        thickness_p[i] = tm + z_score * ts if ts > 0 else tm
+        permeability_p[i] = np.exp(lpm + z_score * lps)
+
+    return (
+        thickness_p.reshape(shape),
+        permeability_p.reshape(shape),
+        transmissivity_p.reshape(shape),
+    )
\ No newline at end of file
diff --git a/src/pythermogis/workflow/utc/utc_properties.py b/src/pythermogis/workflow/utc/configuration.py
similarity index 82%
rename from src/pythermogis/workflow/utc/utc_properties.py
rename to src/pythermogis/workflow/utc/configuration.py
index b9f939956f915275bdb3d071101dea87f3b6e992..483bc2e3e9fcdfb91bb84164d76f16a1e956539b 100644
--- a/src/pythermogis/workflow/utc/utc_properties.py
+++ b/src/pythermogis/workflow/utc/configuration.py
@@ -62,16 +62,16 @@ class UTCConfiguration:
     )
     property_grid_infos: list[PropertyGridInfo] = field(
         default_factory=lambda: [
-            PropertyGridInfo("Permeability", False, "__k.zmap"),
-            PropertyGridInfo("PermeabilityLNSD", False, "__k_lnsd.zmap"),
-            PropertyGridInfo("Porosity", False, "__phi.zmap"),
-            PropertyGridInfo("Thickness", False, "__thick.zmap"),
-            PropertyGridInfo("ThicknessSD", False, "__thick_sd.zmap"),
-            PropertyGridInfo("Depth", False, "__top.zmap"),
-            PropertyGridInfo("NetToGross", False, "__ntg.zmap"),
-            PropertyGridInfo("Temperature", True, "__temperature.zmap"),
-            PropertyGridInfo("HCAccum", True, "__hc_accum.zmap"),
-            PropertyGridInfo("BoundaryShapefile", True, "__BoundaryShapefile.shp"),
+            PropertyGridInfo("permeability", False, "__k.nc"),
+            PropertyGridInfo("permeability_lnsd", False, "__k_ln_sd.nc"),
+            PropertyGridInfo("porosity", False, "__phi.nc"),
+            PropertyGridInfo("thickness", False, "__thick.nc"),
+            PropertyGridInfo("thickness_sd", False, "__thick_sd.nc"),
+            PropertyGridInfo("depth", False, "__top.nc"),
+            PropertyGridInfo("ntg", False, "__ntg.nc"),
+            PropertyGridInfo("temperature", True, "__temperature.nc"),
+            PropertyGridInfo("hc_accum", False, "__hc_accum.nc"),
+            PropertyGridInfo("boundary_shapefile", True, "__BoundaryShapefile.nc"),
         ]
     )
     copy_aquifer_files_info: list[AquiferFile] = field(
@@ -82,15 +82,13 @@ class UTCConfiguration:
             AquiferFile("__points_QC.shp", "__points_QC.shp"),
         ]
     )
-    scenario: str = "basecase"
+    scenario: str = "BaseCase"
     scen_suffix: str = ""
     temp_from_grid: bool = False
     exclude_hc_accum: bool = True
     use_bounding_shape: bool = False
     grid_ext: str = ".nc"
-    p_values: list[float] = field(
-        default_factory=lambda: [10.0, 30.0, 50.0, 70.0, 90.0]
-    )
+    p_values: list[float] = field(default_factory=lambda: [10.0, 30.0, 50.0, 90.0])
     # temp_voxet: 'Voxet' = None
     surface_temperature: float = 10.0
     temp_gradient: float = 31.0
@@ -119,13 +117,13 @@ class UTCConfiguration:
     max_cooling_temp_range: float = 100.0
     hp_minimum_injection_temperature: float = 15.0
     ates_charge_temp: float = 80.0
-    econ_lifetime_years: int = 15
+    econ_lifetime_years: int = 30
     ates_min_flow: float = 0.0
     hp_include_elect_heat_in_power: bool = False
     set_all_values_to_final_rosim_year: bool = False
     max_flow: float = 500.0
     charge_temp: float = 80.0
-    anisotropy: float = 5.0
+    anisotropy: float = 3.0
     filter_fraction: float = 0.8
     salinity_surface: float = 0.0
     salinity_gradient: float = 46.67
@@ -160,19 +158,19 @@ class UTCConfiguration:
     stim_add_skin_prod: float = -3.0
     stimulation_capex: float = 0.5
     hp_calc_cop: bool = True
-    imposed_cop: float = 3.0
-    hp_capex: float = 600.0
-    hp_opex: float = 60.0
+    imposed_cop: float = 4.0
+    hp_capex: float = 200.0
+    hp_opex: float = 10.0
     hp_alternative_heating_price: float = 2.8
     viscosity_mode: ViscosityMode = "batzlewang"
 
     # Economical data
-    economic_lifetime: int = 15
+    economic_lifetime: int = 30
     drilling_time: int = 2
     tax_rate: float = 0.25
     interest_loan: float = 0.05
-    inflation: float = 0.02
-    equity_return: float = 0.07
+    inflation: float = 0.015
+    equity_return: float = 0.145
     debt_equity: float = 0.8
     ecn_eia: float = 0.0
     tolerance_utc_increase: float = 0.0
@@ -182,7 +180,7 @@ class UTCConfiguration:
     elec_purchase_price: float = 8.0
     opex_per_energy: float = 0.19
     opex_per_capex: float = 0.0
-    well_cost_scaling: float = 1.5
+    well_cost_scaling: float = 1.3
     well_cost_const: float = 0.25
     well_cost_z: float = 700.0
     well_cost_z2: float = 0.2
diff --git a/src/pythermogis/workflow/utc/cooling_temp.py b/src/pythermogis/workflow/utc/cooling_temp.py
index cca4291d4fb5b1c36fb054bbd555817e51725e8b..42caf4ddf6e432e736e49a1c8bc44ecd36bfdcec 100644
--- a/src/pythermogis/workflow/utc/cooling_temp.py
+++ b/src/pythermogis/workflow/utc/cooling_temp.py
@@ -6,8 +6,8 @@ from pythermogis.workflow.utc.doublet_utils import calc_lifetime
 from pythermogis.workflow.utc.flow import calculate_volumetric_flow
 
 if TYPE_CHECKING:
+    from pythermogis.workflow.utc.configuration import UTCConfiguration
     from pythermogis.workflow.utc.doublet import DoubletInput
-    from pythermogis.workflow.utc.utc_properties import UTCConfiguration
 
 
 def calculate_cooling_temperature(
diff --git a/src/pythermogis/workflow/utc/doublet.py b/src/pythermogis/workflow/utc/doublet.py
index 61ecb11951f3a2783aa41e23217ed735ed6f8343..e35125d1f5784c93ac35a779acb176c452e3dc2a 100644
--- a/src/pythermogis/workflow/utc/doublet.py
+++ b/src/pythermogis/workflow/utc/doublet.py
@@ -3,6 +3,7 @@ from dataclasses import dataclass
 from typing import NamedTuple
 
 from pythermogis.utils.timer import print_time
+from pythermogis.workflow.utc.configuration import UTCConfiguration
 from pythermogis.workflow.utc.constants import DARCY_SI
 from pythermogis.workflow.utc.cooling_temp import calculate_cooling_temperature
 from pythermogis.workflow.utc.doublet_utils import (
@@ -10,7 +11,6 @@ from pythermogis.workflow.utc.doublet_utils import (
     calculate_injection_temp_with_heat_pump,
 )
 from pythermogis.workflow.utc.pressure import calculate_max_pressure, optimize_pressure
-from pythermogis.workflow.utc.utc_properties import UTCConfiguration
 from pythermogis.workflow.utc.well_distance import optimize_well_distance
 
 EUR_PER_CT_PER_KWH = 0.36
diff --git a/src/pythermogis/workflow/utc/doubletcalc.py b/src/pythermogis/workflow/utc/doubletcalc.py
index 78fc61f211e1b64e96e389ccde13ae731c51672b..8bf300b29499db94b5582e1818a0d98560fdc4fe 100644
--- a/src/pythermogis/workflow/utc/doubletcalc.py
+++ b/src/pythermogis/workflow/utc/doubletcalc.py
@@ -10,8 +10,8 @@ from pythermogis.workflow.utc.rock import get_geothermal_gradient
 from pythermogis.workflow.utc.water import get_salinity
 
 if TYPE_CHECKING:
+    from pythermogis.workflow.utc.configuration import UTCConfiguration
     from pythermogis.workflow.utc.doublet import DoubletInput
-    from pythermogis.workflow.utc.utc_properties import UTCConfiguration
 
 
 INCH_SI = 0.0254
diff --git a/src/pythermogis/workflow/utc/economics.py b/src/pythermogis/workflow/utc/economics.py
index de4329805314623fad11a7aed98ff9de99644f81..53865442baeec9c3aa768d9ee9c16a620550358b 100644
--- a/src/pythermogis/workflow/utc/economics.py
+++ b/src/pythermogis/workflow/utc/economics.py
@@ -9,8 +9,8 @@ from numpy.typing import NDArray
 from pythermogis.workflow.utc.doublet_utils import get_along_hole_length
 
 if TYPE_CHECKING:
+    from pythermogis.workflow.utc.configuration import UTCConfiguration
     from pythermogis.workflow.utc.doublet import DoubletInput
-    from pythermogis.workflow.utc.utc_properties import UTCConfiguration
 
 SECONDS_IN_YEAR = 365 * 24 * 3600
 MJ_TO_GJ = 1e-3
diff --git a/src/pythermogis/workflow/utc/flow.py b/src/pythermogis/workflow/utc/flow.py
index 7fc51d20ea1c6c6cc53a36a3c78889dc9a7293e3..2c964d729f44060d7fd749f4229fd08644e9cee6 100644
--- a/src/pythermogis/workflow/utc/flow.py
+++ b/src/pythermogis/workflow/utc/flow.py
@@ -9,8 +9,8 @@ from pythermogis.workflow.utc.doubletcalc import doubletcalc
 from pythermogis.workflow.utc.heatpump import calculate_heat_pump_performance
 
 if TYPE_CHECKING:
+    from pythermogis.workflow.utc.configuration import UTCConfiguration
     from pythermogis.workflow.utc.doublet import DoubletInput
-    from pythermogis.workflow.utc.utc_properties import UTCConfiguration
 
 
 class VolumetricFlowResults(NamedTuple):
diff --git a/src/pythermogis/workflow/utc/heatpump.py b/src/pythermogis/workflow/utc/heatpump.py
index b2d7a776fa8bbd7932f6c5a27895842a10633d89..86bcb60714c581300bc4f611e221da74873444a0 100644
--- a/src/pythermogis/workflow/utc/heatpump.py
+++ b/src/pythermogis/workflow/utc/heatpump.py
@@ -11,8 +11,8 @@ from pythermogis.workflow.utc.water import (
 )
 
 if TYPE_CHECKING:
+    from pythermogis.workflow.utc.configuration import UTCConfiguration
     from pythermogis.workflow.utc.doublet import DoubletInput
-    from pythermogis.workflow.utc.utc_properties import UTCConfiguration
 
 
 class HeatPumpPerformanceResults(NamedTuple):
diff --git a/src/pythermogis/workflow/utc/pressure.py b/src/pythermogis/workflow/utc/pressure.py
index 244bab4d3ea0b1399ba07be67f5a7152c3d53218..6c2c9e4fb94cbbe52479b819f69b6da148986052 100644
--- a/src/pythermogis/workflow/utc/pressure.py
+++ b/src/pythermogis/workflow/utc/pressure.py
@@ -6,8 +6,8 @@ from pythermogis.workflow.utc.economics import calculate_economics
 from pythermogis.workflow.utc.flow import calculate_volumetric_flow
 
 if TYPE_CHECKING:
+    from pythermogis.workflow.utc.configuration import UTCConfiguration
     from pythermogis.workflow.utc.doublet import DoubletInput
-    from pythermogis.workflow.utc.utc_properties import UTCConfiguration
 
 
 def calculate_max_pressure(
diff --git a/src/pythermogis/workflow/utc/stats.py b/src/pythermogis/workflow/utc/stats.py
new file mode 100644
index 0000000000000000000000000000000000000000..4ac8462d12cf3530f38c1e87147796a2f1564d46
--- /dev/null
+++ b/src/pythermogis/workflow/utc/stats.py
@@ -0,0 +1,12 @@
+import numpy as np
+from scipy.stats import norm
+
+
+def lognormal_quantile(mean, sd, p):
+    z = norm.ppf(1 - p / 100)
+    return mean * np.exp(sd * z)
+
+
+def normal_quantile(mean, sd, p):
+    z = norm.ppf(1 - p / 100)
+    return mean + sd * z
diff --git a/src/pythermogis/workflow/utc/utc.py b/src/pythermogis/workflow/utc/utc.py
new file mode 100644
index 0000000000000000000000000000000000000000..129cabaf4bce342e6e469c56eecd323d4ab3b351
--- /dev/null
+++ b/src/pythermogis/workflow/utc/utc.py
@@ -0,0 +1,229 @@
+import time
+from pathlib import Path
+
+import numpy as np
+import xarray as xr
+from scipy.special import ndtri
+
+from pythermogis.transmissivity.calculate_thick_perm_trans import (
+    calculate_transmissivity,
+)
+from pythermogis.workflow.utc.configuration import UTCConfiguration
+from pythermogis.workflow.utc.doublet import (
+    DoubletInput,
+    DoubletOutput,
+    calculate_doublet_performance,
+)
+
+OUTPUT_NAMES = list(DoubletOutput.__annotations__.keys())
+NAN_OUTPUTS = DoubletOutput(*[np.nan] * len(OUTPUT_NAMES)) # type: ignore[arg-type]
+ZERO_OUTPUTS = DoubletOutput(*[0.0] * len(OUTPUT_NAMES)) # type: ignore[arg-type]
+
+
+def run_utc_workflow(config: UTCConfiguration) -> xr.DataTree:
+    root = xr.DataTree()
+    base = Path(config.input_data_dir)
+
+    temperature_model = xr.open_dataset(
+        base / "NetherlandsTemperatureModel_extended.nc"
+    ).transpose("y", "x", "z")
+
+    for aquifer in config.aquifers:
+        aquifer_ds = xr.Dataset()
+
+        for gridinfo in config.property_grid_infos:
+            if gridinfo.optional:
+                continue
+
+            filename = f"{aquifer}{gridinfo.postfix}"
+            fullpath = base / filename
+
+            if not fullpath.exists():
+                raise FileNotFoundError(f"Required grid not found: {fullpath}")
+
+            ds = xr.open_dataset(fullpath)
+
+            varnames = [v for v in ds.data_vars if v != "oblique_stereographic"]
+            if len(varnames) != 1:
+                raise ValueError(
+                    f"Expected exactly one property variable in"
+                    f" {fullpath}, found {varnames}"
+                )
+
+            varname = varnames[0]
+
+            aquifer_ds[gridinfo.name] = ds[varname]
+
+        root[aquifer] = xr.DataTree(dataset=aquifer_ds, name=aquifer)
+
+    for aquifer in root.children:
+        print(f"\nProcessing aquifer: {aquifer}")
+
+        start = time.perf_counter()
+
+        aquifer_ds = root[aquifer].to_dataset()
+        updated_ds = compute_results_for_aquifer(
+            aquifer_ds, aquifer, config, temperature_model
+        )
+        root[aquifer] = xr.DataTree(dataset=updated_ds, name=aquifer)
+
+        end = time.perf_counter()
+        elapsed = end - start
+
+        print(f"Time required for aquifer {aquifer}: {elapsed:.2f} seconds.")
+
+    if config.results_dir != "":
+        zarr_path = f"{config.results_dir}/ROSL_ROSLU_test.zarr"
+        root.to_zarr(zarr_path, mode="w")
+
+    return root
+
+
+def compute_results_for_aquifer(
+    aquifer_ds: xr.Dataset,
+    aquifer_name: str,
+    config: UTCConfiguration,
+    temperature_model: xr.Dataset,
+):
+    # apply hc mask
+    hc_mask = aquifer_ds["hc_accum"] != 0
+    vars_to_mask = [
+        "thickness",
+        "ntg",
+        "depth",
+        "porosity",
+    ]
+
+    for v in vars_to_mask:
+        aquifer_ds[v] = aquifer_ds[v].where(hc_mask)
+
+    # calc temperature grid
+    mid_depth = -(aquifer_ds["depth"] + 0.5 * aquifer_ds["thickness"])
+    temp_xy_aligned = temperature_model["temperature"].interp(
+        x=aquifer_ds.x, y=aquifer_ds.y, method="linear"
+    )
+    temperature = temp_xy_aligned.interp(z=mid_depth, method="linear")
+
+    aquifer_ds["temperature"] = temperature
+
+    for p_value in config.p_values:
+        # calc transmissivity(_with_ntg)
+        stoch_results = apply_stochastics(aquifer_ds, p_value)
+        aquifer_ds["transmissivity"] = stoch_results["transmissivity"]
+        aquifer_ds["transmissivity_with_ntg"] = stoch_results["transmissivity_with_ntg"]
+        aquifer_ds["thickness"] = stoch_results["thickness"]
+        aquifer_ds["permeability"] = stoch_results["permeability"]
+
+        results = xr.apply_ufunc(
+            cell_calculation,
+            1.0e30,
+            aquifer_ds["thickness"],
+            aquifer_ds["transmissivity"],
+            aquifer_ds["transmissivity_with_ntg"],
+            aquifer_ds["ntg"],
+            aquifer_ds["depth"],
+            aquifer_ds["porosity"],
+            aquifer_ds["temperature"],
+            kwargs={"config": config},
+            input_core_dims=[[]] * 8,
+            output_core_dims=[[] for _ in OUTPUT_NAMES],
+            vectorize=True,
+            dask="parallelized",
+            output_dtypes=[np.float64] * len(OUTPUT_NAMES),
+        )
+
+        for name, result in zip(OUTPUT_NAMES, results, strict=True):
+            aquifer_ds[f"{name}_p{p_value}"] = result
+
+    aquifer_ds.compute()
+
+    print(f"Computed results for {aquifer_name}")
+
+    return aquifer_ds
+
+
+def apply_stochastics(
+    aquifer_ds: xr.Dataset,
+    p_value: float,
+    n_samples: int = 10_000,
+) -> xr.Dataset:
+
+    q = 1.0 - p_value / 100.0
+    z = ndtri(q)
+
+    thickness_p, permeability_p, transmissivity_p = calculate_transmissivity(
+        aquifer_ds["thickness"].values,
+        aquifer_ds["thickness_sd"].values,
+        np.log(aquifer_ds["permeability"].values),
+        aquifer_ds["permeability_lnsd"].values,
+        q,
+        z,
+        n_samples,
+    )
+
+    transmissivity_with_ntg = transmissivity_p * aquifer_ds["ntg"] / 1000.0
+    transmissivity_with_ntg = transmissivity_with_ntg.where(
+        transmissivity_with_ntg >= 0
+    )
+
+    return xr.Dataset(
+        {
+            "thickness": (aquifer_ds["thickness"].dims, thickness_p),
+            "permeability": (aquifer_ds["thickness"].dims, permeability_p),
+            "transmissivity": (aquifer_ds["thickness"].dims, transmissivity_p),
+            "transmissivity_with_ntg": transmissivity_with_ntg,
+        },
+        coords=aquifer_ds.coords,
+    )
+
+
+def cell_calculation(
+    unknown_input_value: float,
+    thickness: float,
+    transmissivity: float,
+    transmissivity_with_ntg: float,
+    ntg: float,
+    depth: float,
+    porosity: float,
+    temperature: float,
+    config: UTCConfiguration,
+) -> DoubletOutput:
+    inputs = [
+        unknown_input_value,
+        thickness,
+        transmissivity,
+        transmissivity_with_ntg,
+        ntg,
+        depth,
+        porosity,
+        temperature,
+    ]
+    if any(np.isnan(v) for v in inputs):
+        return NAN_OUTPUTS
+
+    if transmissivity_with_ntg < config.kh_cutoff:
+        return ZERO_OUTPUTS
+
+    doublet_input = DoubletInput(
+        unknown_input_value=unknown_input_value,
+        thickness=thickness,
+        transmissivity=transmissivity,
+        transmissivity_with_ntg=transmissivity_with_ntg,
+        ntg=ntg,
+        depth=depth,
+        porosity=porosity / 100,
+        temperature=temperature,
+    )
+
+    try:
+        result = calculate_doublet_performance(config, doublet_input)
+    except ValueError:
+        return NAN_OUTPUTS
+
+    if result is None:
+        return NAN_OUTPUTS
+
+    if result.utc > 1000:
+        result = result._replace(utc=1000)
+
+    return result
diff --git a/src/pythermogis/workflow/utc/well_distance.py b/src/pythermogis/workflow/utc/well_distance.py
index 4a585274297843fa5249167a6b9fc440d8e26528..f84e75be96cd01f04219507429dfcb924c44e321 100644
--- a/src/pythermogis/workflow/utc/well_distance.py
+++ b/src/pythermogis/workflow/utc/well_distance.py
@@ -9,8 +9,8 @@ from pythermogis.workflow.utc.doublet_utils import calc_lifetime
 from pythermogis.workflow.utc.flow import calculate_volumetric_flow
 
 if TYPE_CHECKING:
+    from pythermogis.workflow.utc.configuration import UTCConfiguration
     from pythermogis.workflow.utc.doublet import DoubletInput
-    from pythermogis.workflow.utc.utc_properties import UTCConfiguration
 
 
 def optimize_well_distance_original(
diff --git a/tests/utc/test_calculate_volumetric_flow.py b/tests/utc/test_calculate_volumetric_flow.py
index f3059727e750f4629d42d09c788abb5865c8dd34..aedbc493055ac508230bd013ef8cad7d1781f067 100644
--- a/tests/utc/test_calculate_volumetric_flow.py
+++ b/tests/utc/test_calculate_volumetric_flow.py
@@ -2,7 +2,7 @@ import numpy as np
 
 from pythermogis.workflow.utc.doublet import DoubletInput
 from pythermogis.workflow.utc.flow import calculate_volumetric_flow
-from pythermogis.workflow.utc.utc_properties import UTCConfiguration
+from pythermogis.workflow.utc.configuration import UTCConfiguration
 
 
 def test_calculate_volumetric_flow():
diff --git a/tests/utc/test_doublet.py b/tests/utc/test_doublet.py
index e42d93acbc41a18effb6747f9451640e18258733..e370b419a7579f02f3731ffc328f93de6e95c508 100644
--- a/tests/utc/test_doublet.py
+++ b/tests/utc/test_doublet.py
@@ -4,7 +4,7 @@ import numpy as np
 
 
 from pythermogis.workflow.utc.doublet import DoubletInput, calculate_doublet_performance
-from pythermogis.workflow.utc.utc_properties import UTCConfiguration
+from pythermogis.workflow.utc.configuration import UTCConfiguration
 
 
 def test_calculate_doublet_performance_precise():
@@ -42,12 +42,12 @@ def test_calculate_doublet_performance_precise():
     rtol = 0.005 # accurate to 0.5%
     assert np.isclose(result.flow, 227.2757568359375, rtol=rtol)
     assert np.isclose(result.pres, 60, rtol=rtol)
-    assert np.isclose(result.utc, 6.616096470753937, rtol=rtol)
+    assert np.isclose(result.utc, 5.885437310055949, rtol=rtol)
     assert np.isclose(result.welld, 1159.17968, rtol=rtol)
     assert np.isclose(result.power, 8.636903762817383, rtol=rtol)
     assert np.isclose(result.cop, 13.627557754516602, rtol=rtol)
-    assert np.isclose(result.var_opex, -7.510325908660889, rtol=rtol)
-    assert np.isclose(result.fixed_opex, -11.227973937988281, rtol=rtol)
+    assert np.isclose(result.var_opex, -16.189716379776353, rtol=rtol)
+    assert np.isclose(result.fixed_opex, -24.199008115259968, rtol=rtol)
 
 def test_calculate_doublet_performance_approximate():
     # Arrange: instantiate default UTCConfiguration
@@ -86,12 +86,12 @@ def test_calculate_doublet_performance_approximate():
     rtol = 0.01 # accurate to 1%
     assert np.isclose(result.flow, 227.2757568359375, rtol=rtol)
     assert np.isclose(result.pres, 60, rtol=rtol)
-    assert np.isclose(result.utc, 6.616096470753937, rtol=rtol)
+    assert np.isclose(result.utc, 5.885437310055949, rtol=rtol)
     assert np.isclose(result.welld, 1159.17968, rtol=rtol)
     assert np.isclose(result.power, 8.636903762817383, rtol=rtol)
     assert np.isclose(result.cop, 13.627557754516602, rtol=rtol)
-    assert np.isclose(result.var_opex, -7.510325908660889, rtol=rtol)
-    assert np.isclose(result.fixed_opex, -11.227973937988281, rtol=rtol)
+    assert np.isclose(result.var_opex, -16.189716379776353, rtol=rtol)
+    assert np.isclose(result.fixed_opex, -24.199008115259968, rtol=rtol)
 
 def test_calculate_doublet_performance():
     # 85ish it/s
@@ -140,3 +140,26 @@ def test_calculate_doublet_performance():
         f"{n_sims} simulations took: {time_elapsed:.1f} seconds\n"
         f"{n_sims/time_elapsed:.1f} simulations per second"
     )
+
+
+def test_why_does_this_fail():
+    props = UTCConfiguration(
+        segment_length=1,
+        dh_return_temp=40
+    )
+
+    # Create a minimal valid DoubletInput
+    input_data = DoubletInput(
+        unknown_input_value=-9999,
+        thickness=5.259,
+        transmissivity=1239.250,
+        transmissivity_with_ntg=1.032,
+        ntg=0.8331,
+        depth=852.969,
+        porosity=0.22168,
+        temperature=39.30,
+    )
+
+    # Act
+    results = calculate_doublet_performance(props, input_data)
+    print(results)
diff --git a/tests/utc/test_doubletcalc.py b/tests/utc/test_doubletcalc.py
index e49d5d10925f030c41ca77b3e45b39ee32d0e8c7..ce52c4f97bd7473e674925ee80bac8f292085d4a 100644
--- a/tests/utc/test_doubletcalc.py
+++ b/tests/utc/test_doubletcalc.py
@@ -5,7 +5,7 @@ import pytest
 
 from pythermogis.workflow.utc.doublet import DoubletInput
 from pythermogis.workflow.utc.doubletcalc import doubletcalc
-from pythermogis.workflow.utc.utc_properties import UTCConfiguration
+from pythermogis.workflow.utc.configuration import UTCConfiguration
 
 
 def test_doubletcalc():
diff --git a/tests/utc/test_properties.py b/tests/utc/test_properties.py
index ab98eb17c08247970d6bd8f91131fd2721919c52..06fbc9560ce0de1ebf8d9df61645836c977fb2f8 100644
--- a/tests/utc/test_properties.py
+++ b/tests/utc/test_properties.py
@@ -1,4 +1,4 @@
-from pythermogis.workflow.utc.utc_properties import UTCConfiguration
+from pythermogis.workflow.utc.configuration import UTCConfiguration
 
 
 def test_utc_configuration_instantiation():
@@ -10,20 +10,20 @@ def test_utc_configuration_instantiation():
     assert isinstance(cfg.copy_aquifer_files_info, list)
     assert cfg.n_threads == 1
     assert cfg.is_ates is False
-    assert cfg.scenario == "basecase"
+    assert cfg.scenario == "BaseCase"
     assert cfg.viscosity_mode == "batzlewang"
     assert cfg.surface_temperature == 10.0
     assert cfg.temp_gradient == 31.0
     assert 30.0 in cfg.p_values
-    assert cfg.p_values == [10.0, 30.0, 50.0, 70.0, 90.0]
-    assert cfg.property_grid_infos[0].name == "Permeability"
+    assert cfg.p_values == [10.0, 30.0, 50.0, 90.0]
+    assert cfg.property_grid_infos[0].name == "permeability"
     assert cfg.property_grid_infos[0].optional is False
-    assert cfg.property_grid_infos[0].postfix.endswith(".zmap")
+    assert cfg.property_grid_infos[0].postfix.endswith(".nc")
     assert len(cfg.aquifers) > 10
     assert "NMRFT" in cfg.aquifers
     assert cfg.petrel_output_dir is None
     assert cfg.tax_rate == 0.25
     assert cfg.interest_loan == 0.05
-    assert cfg.economic_lifetime == 15
+    assert cfg.economic_lifetime == 30
 
 
diff --git a/tests/utc/test_rosl_roslu.py b/tests/utc/test_rosl_roslu.py
new file mode 100644
index 0000000000000000000000000000000000000000..39428d0ca4a7039d63ad8bdc15b89bc8cc007bdd
--- /dev/null
+++ b/tests/utc/test_rosl_roslu.py
@@ -0,0 +1,24 @@
+# import matplotlib.pyplot as plt
+#
+# from pythermogis.workflow.utc.configuration import UTCConfiguration
+# from pythermogis.workflow.utc.utc import run_utc_workflow
+#
+# def test_rosl_roslu():
+#     """
+#     Integration test that runs the whole ROSL_ROSLU aquifer.
+#     The input is identical to the java 2.5.3 input.
+#     The output is compared to the java output.
+#     """
+#     config = UTCConfiguration(
+#         input_data_dir="C:/Users/knappersfy/work/thermogis/pythermogis/workdir/ROSL_ROSLU/input",
+#         results_dir="C:/Users/knappersfy/work/thermogis/pythermogis/workdir/ROSL_ROSLU/output",
+#         aquifers=["ROSL_ROSLU"],
+#         segment_length=1,
+#         p_values=[50] # For now only calculating this value, because it is way faster than 50
+#     )
+#     result = run_utc_workflow(config)
+#
+#     result.ROSL_ROSLU.utc_p50.plot() # should match p value in config
+#     plt.show()
+#
+#     print(result)
\ No newline at end of file
diff --git a/tests/utc/test_well_distance_optimizer.py b/tests/utc/test_well_distance_optimizer.py
index 00401228f3d88d7f9051a2bcfe6dba0af8f2f36c..64ab18ea58f343fc0ae8b08a114aa7f4de63006d 100644
--- a/tests/utc/test_well_distance_optimizer.py
+++ b/tests/utc/test_well_distance_optimizer.py
@@ -1,7 +1,7 @@
 import numpy as np
 
 from pythermogis.workflow.utc.doublet import DoubletInput
-from pythermogis.workflow.utc.utc_properties import UTCConfiguration
+from pythermogis.workflow.utc.configuration import UTCConfiguration
 from pythermogis.workflow.utc.well_distance import (
     optimize_well_distance,
     optimize_well_distance_original,