{'fraction_non_alphanumeric': 0.009115281501340482, 'fraction_numerical': 0.0, 'mean_word_length': 5.501742160278746, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Novel Approach to Analyze Fracture Properties Utilizing Advanced Mud Logging


 Mud logging, in essence, is a wellsite operation that investigates, records, and analyzes measurements obtained from the circulating drilling fluid that results in the measurement of cuttings and gas. It plays a vital role in the identification of downhole geological conditions, such as hydrocarbon presence and stratigraphy along with monitoring drilling conditions, to ensure safety of operations and improve efficiency. The objective of this paper is to utilize advanced mud logging analysis characteristics to establish a workflow to potentially identify fractures along an interval. Helium is used as the correlation parameter to potentially indicate fractures along the intended formation. Advanced mud logging provides a quantitative hydrocarbon measurement from the drilling mud rather than the qualitative measurements that regular mudlogging provides. Helium is one of the major components that advanced mudlogging provides and acts as an indicator of permeability in a formation. The process starts with a novel method to utilize helium to be a correlator of fractures within a formation in terms of identification and measurements along with tracking the fracture with time. The combination between current formation imaging procedures and helium readings from mud logs is proven to be a key potential indicator to establish a fracture identification pattern.
 The utility of the correlated helium readings from mud logging and fractures from formation image logs is a major breakthrough into identifying formation fracture features. Tracking changes of such features in which mud logging readings are used directly as potential indicators of fractures in an anticipated well. Loss of circulation prediction and LCM designs are enhanced directly by this extra knowledge.