diff --git a/ocf_datapipes/load/satellite.py b/ocf_datapipes/load/satellite.py
index 150216132..44ba7f557 100644
--- a/ocf_datapipes/load/satellite.py
+++ b/ocf_datapipes/load/satellite.py
@@ -83,7 +83,7 @@ def open_sat_data(
         ds = open_sat_data(zarr_paths)
         ```
     """
-    _log.info("Opening satellite data: %s", zarr_path)
+    _log.info(f"Opening satellite data: %s, {use_15_minute_data_if_needed=}", zarr_path)
 
     # Silence the warning about large chunks.
     # Alternatively, we could set this to True, but that slows down loading a Satellite batch
@@ -113,6 +113,8 @@ def open_sat_data(
         dataset = dataset.load()
         _log.debug("Resampling 15 minute data to 5 mins")
         dataset = dataset.resample(time="5T").interpolate("linear")
+    else:
+        _log.debug("Not using 15 minute data")
 
     # Remove data coordinate dimensions if they exist
     if "x_geostationary_coordinates" in dataset:
diff --git a/ocf_datapipes/training/pvnet.py b/ocf_datapipes/training/pvnet.py
index fed6ab40b..c8f0578ee 100644
--- a/ocf_datapipes/training/pvnet.py
+++ b/ocf_datapipes/training/pvnet.py
@@ -228,6 +228,7 @@ def _get_datapipes_dict(
         use_hrv=False,
         use_nwp=not block_nwp,  # Only loaded if we aren't replacing them with zeros
         use_topo=False,
+        production=production,
     )
     if production:
         configuration: Configuration = datapipes_dict["config"]
@@ -636,9 +637,26 @@ def check_nans_in_satellite_data(batch: NumpyBatch) -> NumpyBatch:
     if np.any(np.isnan(batch[BatchKey.satellite_actual])):
         logger.error("Found nans values in satellite data")
 
-        for t in range(batch[BatchKey.satellite_actual].shape[1]):
-            if np.any(np.isnan(batch[BatchKey.satellite_actual][:, t])):
-                logger.error(f"Found nans values in satellite data at time index {t}")
+        logger.error(batch[BatchKey.satellite_actual].shape)
+
+        # loop over time and channels
+        for dim in [0, 1]:
+            for t in range(batch[BatchKey.satellite_actual].shape[dim]):
+                if dim == 0:
+                    sate_data_one_step = batch[BatchKey.satellite_actual][t]
+                else:
+                    sate_data_one_step = batch[BatchKey.satellite_actual][:, t]
+                nans = np.isnan(sate_data_one_step)
+
+                if np.any(nans):
+                    percent_nans = np.sum(nans) / np.prod(sate_data_one_step.shape) * 100
+
+                    logger.error(
+                        f"Found nans values in satellite data at index {t} ({dim=}). "
+                        f"{percent_nans}% of values are nans"
+                    )
+                else:
+                    logger.error(f"Found no nans values in satellite data at index {t} {dim=}")
 
         raise ValueError("Found nans values in satellite data")