diff --git a/src/fetch/orderbook.py b/src/fetch/orderbook.py
index 82eb4e1b..974e97cd 100644
--- a/src/fetch/orderbook.py
+++ b/src/fetch/orderbook.py
@@ -12,9 +12,12 @@
 from sqlalchemy import create_engine
 from sqlalchemy.engine import Engine
 
+from src.logger import set_log
 from src.models.block_range import BlockRange
 from src.utils import open_query
 
+log = set_log(__name__)
+
 MAX_PROCESSING_DELAY = 10
 
 
@@ -96,14 +99,13 @@ def get_order_rewards(cls, block_range: BlockRange) -> DataFrame:
         )
 
         # Solvers do not appear in both environments!
-        assert set(prod.solver).isdisjoint(set(barn.solver)), "solver overlap!"
-        if not prod.empty and not barn.empty:
-            return pd.concat([prod, barn])
-        if not prod.empty:
-            return prod.copy()
-        if not barn.empty:
-            return barn.copy()
-        return pd.DataFrame()
+        if set(prod.solver).isdisjoint(set(barn.solver)):
+            log.warning(
+                f"solver overlap in {block_range}: solvers "
+                f"{set(prod.solver).intersection(set(barn.solver))} part of both prod and barn"
+            )
+
+        return pd.concat([prod, barn])
 
     @classmethod
     def get_batch_rewards(cls, block_range: BlockRange) -> DataFrame:
@@ -143,14 +145,13 @@ def get_batch_rewards(cls, block_range: BlockRange) -> DataFrame:
         )
 
         # Solvers do not appear in both environments!
-        assert set(prod.solver).isdisjoint(set(barn.solver)), "solver overlap!"
-        if not prod.empty and not barn.empty:
-            return pd.concat([prod, barn])
-        if not prod.empty:
-            return prod.copy()
-        if not barn.empty:
-            return barn.copy()
-        return pd.DataFrame()
+        if set(prod.solver).isdisjoint(set(barn.solver)):
+            log.warning(
+                f"solver overlap in {block_range}: solvers "
+                f"{set(prod.solver).intersection(set(barn.solver))} part of both prod and barn"
+            )
+
+        return pd.concat([prod, barn])
 
     @classmethod
     def get_app_hashes(cls) -> DataFrame: