Added section on computational considerations

docs/getting_started/howto/adaptive_localization.ipynb

@@ -1,5 +1,5 @@
 {
- "cells": [
+    "cells": [
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -34,7 +34,7 @@
    "source": [
     "# Adaptive Localization\n",
     "\n",
-    "Parameter estimation using few samples (realizations) leads to sampling errors and spurious correlations (see Section 1.3), which can lead to inaccurately strong updates during the estimation process.\n",
+    "Parameter estimation using few samples (realizations) leads to sampling errors and spurious correlations (see section below), which can lead to inaccurately strong updates during the estimation process.\n",
     "A strong update, characterized by a posterior with low variance, can be misleading - essentially leading to confident but potentially incorrect conclusions.\n",
     "Localization is a widely used method to mitigate this.\n",
     "\n",
@@ -187,6 +187,19 @@
     "![](ert_screenshot_adaptive_loc.png)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "60dc9385-1f28-415d-a5b3-15cedce07f65",
+   "metadata": {},
+   "source": [
+    "## Computational Considerations\n",
+    "\n",
+    "Be aware that adaptive localization comes with significant computational costs, which depend on two factors:\n",
+    "\n",
+    "    - The number of parameters: More parameters lead to longer run times.\n",
+    "    - The correlation threshold: A higher threshold reduces computational time.\n"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "d6f3bb27-cbad-41ff-a93f-d8673c5ad5ed",