diff --git a/demos/getting_started_3.py b/demos/getting_started_3.py
index 3451c5a2442dfc94f222f1bba017c0547a445cec..45be6b05bdfeac90c4da9931a62b095b0f9679f4 100644
--- a/demos/getting_started_3.py
+++ b/demos/getting_started_3.py
@@ -58,14 +58,14 @@ if __name__ == '__main__':
     position_space = ift.RGSpace([128, 128])
 
     cfmaker = ift.CorrelatedFieldMaker.make(
-        offset_mean = 0.,  # 0.
-        offset_variation_mean =   1e-3,  # 1e-3
-        offset_variation_stddev = 1e-6,  # 1e-6
+        offset_mean =      0.0,  # 0.
+        offset_std_mean = 1e-3,  # 1e-3
+        offset_std_std =  1e-6,  # 1e-6
         prefix = '')
 
     fluctuations_dict = {
         # Amplitude of the fluctuations
-        'fluctuations_mean':   2.0,   # 1.0
+        'fluctuations_mean':   2.0,  # 1.0
         'fluctuations_stddev': 1.0,  # 1e-2
 
         # Smooth variation speed
diff --git a/nifty6/library/correlated_fields.py b/nifty6/library/correlated_fields.py
index 6d703d6f6f5aca1b0ad12505ce24d57861b3e813..4ce7007ba7350a53f2e63f584f28352900804946 100644
--- a/nifty6/library/correlated_fields.py
+++ b/nifty6/library/correlated_fields.py
@@ -364,16 +364,33 @@ class CorrelatedFieldMaker:
         self._total_N = total_N
 
     @staticmethod
-    def make(offset_mean, offset_variation_mean, offset_variation_stddev, prefix,
+    def make(offset_mean, offset_std_mean, offset_std_std, prefix,
              total_N=0,
              dofdex=None):
+        """Returns a CorrelatedFieldMaker object.
+
+        Parameters
+        ----------
+        offset_mean : float
+            Mean offset from zero of the correlated field to be made.
+        offset_std_mean : float
+            Mean standard deviation of the offset value.
+        offset_std_std : float
+            Standard deviation of the stddev of the offset value.
+        prefix : string
+            Prefix to the names of the domains of the cf operator to be made.
+        total_N : integer
+            ?
+        dofdex : np.array
+            ?
+        """
         if dofdex is None:
             dofdex = np.full(total_N, 0)
         elif len(dofdex) != total_N:
             raise ValueError("length of dofdex needs to match total_N")
         N = max(dofdex) + 1 if total_N > 0 else 0
-        zm = _LognormalMomentMatching(offset_variation_mean,
-                                      offset_variation_stddev,
+        zm = _LognormalMomentMatching(offset_std_mean,
+                                      offset_std_std,
                                       prefix + 'zeromode',
                                       N)
         if total_N > 0: