diff --git a/mth5/timeseries/channel_ts.py b/mth5/timeseries/channel_ts.py
index 1ee860f0..3bc16073 100644
--- a/mth5/timeseries/channel_ts.py
+++ b/mth5/timeseries/channel_ts.py
@@ -1078,7 +1078,10 @@ def get_response_correction_operation_and_units(self):
         return calibration_operation, calibrated_units
 
 
-    def remove_instrument_response(self, **kwargs):
+    def remove_instrument_response(self,
+                                   include_decimation=True,
+                                   include_delay=False,
+                                   **kwargs):
         """
         Remove instrument response from the given channel response filter
 
@@ -1093,6 +1096,13 @@ def remove_instrument_response(self, **kwargs):
             7) undo time window
             8) bandpass
 
+        :param include_decimation: Include decimation in response,
+         defaults to True
+        :type include_decimation: bool, optional
+        :param include_delay: include delay in complex response,
+         defaults to False
+        :type include_delay: bool, optional
+
         **kwargs**
 
         :param plot: to plot the calibration process [ False | True ]
@@ -1117,6 +1127,8 @@ def remove_instrument_response(self, **kwargs):
         :type bandpass: dictionary
 
         """
+        def bool_flip(x):
+            return bool(int(x)-1)
 
         calibrated_ts = ChannelTS()
         calibrated_ts.__dict__.update(self.__dict__)
@@ -1126,6 +1138,11 @@ def remove_instrument_response(self, **kwargs):
                 "No filters to apply to calibrate time series data"
             )
             return calibrated_ts
+
+        # Make a list of the filters whose response will be removed.
+        # We make the list here so that we have access to the indices to flip
+        filters_to_remove, indices_to_flip = self.channel_response_filter.get_list_of_filters_to_remove(include_decimation=include_decimation, include_delay=include_delay)
+
         remover = RemoveInstrumentResponse(
             self.ts,
             self.time_index,
@@ -1135,7 +1152,8 @@ def remove_instrument_response(self, **kwargs):
         )
 
         calibration_operation, calibrated_units = self.get_response_correction_operation_and_units()
-        calibrated_ts.ts = remover.remove_instrument_response(operation=calibration_operation)
+        calibrated_ts.ts = remover.remove_instrument_response(filters_to_remove=filters_to_remove,
+                                                              operation=calibration_operation)
 
         # change applied booleans
         # TODO use invert on bool, instead of direct assignement to False
diff --git a/mth5/timeseries/ts_filters.py b/mth5/timeseries/ts_filters.py
index 08c6a1d3..a8a3d36d 100644
--- a/mth5/timeseries/ts_filters.py
+++ b/mth5/timeseries/ts_filters.py
@@ -187,6 +187,15 @@ def __init__(
         channel_response_filter,
         **kwargs,
     ):
+        """
+
+        :param ts:
+        :param time_array:
+        :param sample_interval:
+        :param channel_response_filter:
+        :param filters_to_remove: optional list of specific filters to remove.  If not provided, filters will be
+        taken from channel_response_filter.
+        """
         self.logger = logger
         self.ts = ts
         self.time_array = time_array
@@ -205,7 +214,7 @@ def __init__(
         self.nrows = None
         self.subplot_dict = {}
         self.include_decimation = True
-        self.include_time_delay = False
+        self.include_delay = False
 
         for key, value in kwargs.items():
             setattr(self, key, value)
@@ -475,7 +484,8 @@ def _get_subplot_count(self):
     def remove_instrument_response(self,
                                    operation="divide",
                                    include_decimation=None,
-                                   include_time_delay=None):
+                                   include_delay=None,
+                                   filters_to_remove=[]):
         """
         Remove instrument response following the recipe provided
 
@@ -484,11 +494,20 @@ def remove_instrument_response(self,
 
         """
         # if filters to include not specified, get from self
-        if include_decimation is None:
-            include_decimation = self.include_decimation
-        if include_time_delay is None:
-            include_time_delay = self.include_time_delay
-            
+        if not filters_to_remove:
+            self.logger.debug("No explicit list of filters was passed to remove")
+            self.logger.debug("Will determine filters to remove ... ")
+            if include_decimation is None:
+                include_decimation = self.include_decimation
+            if include_delay is None:
+                include_delay = self.include_delay
+            filters_to_remove, _ = self.channel_response_filter.get_list_of_filters_to_remove(
+                include_decimation=include_decimation, include_delay=include_delay)
+            if filters_to_remove is []:
+                raise ValueError("There are no filters in channel_response to remove")
+
+
+
         ts = np.copy(self.ts)
         f = np.fft.rfftfreq(ts.size, d=self.sample_interval)
         step = 1
@@ -537,20 +556,15 @@ def remove_instrument_response(self,
             ts = self.apply_zero_pad(ts)
             self.logger.debug(f"Step {step}: Applying Zero Padding")
             step += 1
-        # get the real frequencies of the FFT
+        # get the real frequencies of the FFT -- zero pad may have changed ts.size
         f = np.fft.rfftfreq(ts.size, d=self.sample_interval)
 
-        if self.channel_response_filter.filters_list is []:
-            raise ValueError("There are no filters in channel_response to remove")
-        if self.channel_response_filter.correction_operation == "multiply":
-            inverse_filters = [x.inverse() for x in self.channel_response_filter.filters_list]
-            self.channel_response_filter.filters_list = inverse_filters
         # compute the complex response given the frequency range of the FFT
         # the complex response assumes frequencies are in reverse order and flip them on input
         # so we need to flip the complex reponse so it aligns with the fft.
         cr = self.channel_response_filter.complex_response(f,
-                                                           include_decimation=include_decimation,
-                                                           include_time_delay=include_time_delay)[::-1]
+                                                           filters_list=filters_to_remove,
+                                                           )[::-1]
         # remove the DC term at frequency == 0
         cr[-1] = abs(cr[-2]) + 0.0j