In-situ Water quality monitoring in Oil and Gas operations

TL;DR

This paper introduces a novel Water Quality Enhanced Index (WQEI) model that improves satellite-based monitoring of small water bodies, enabling efficient large-scale water quality assessment crucial for oil and gas operations.

Contribution

The paper presents a new WQEI model that effectively detects contamination in small water bodies using satellite data, overcoming limitations of existing index-based methods.

Findings

WQEI correlates well with laboratory turbidity measurements.

Application of WQEI with Landsat 8 data achieves high accuracy in large regions.

The method supports better water resource management in oil and gas operations.

Abstract

From agriculture to mining, to energy, surface water quality monitoring is an essential task. As oil and gas operators work to reduce the consumption of freshwater, it is increasingly important to actively manage fresh and non-fresh water resources over the long term. For large-scale monitoring, manual sampling at many sites has become too time-consuming and unsustainable, given the sheer number of dispersed ponds, small lakes, playas, and wetlands over a large area. Therefore, satellite-based environmental monitoring presents great potential. Many existing satellite-based monitoring studies utilize index-based methods to monitor large water bodies such as rivers and oceans. However, these existing methods fail when monitoring small ponds-the reflectance signal received from small water bodies is too weak to detect. To address this challenge, we propose a new Water Quality Enhanced Index (WQEI) Model, which is designed to enable users to determine contamination levels in water bodies with weak reflectance patterns. Our results show that 1) WQEI is a good indicator of water turbidity validated with 1200 water samples measured in the laboratory, and 2) by applying our method to commonly available satellite data (e.g. LandSat8), one can achieve high accuracy water quality monitoring efficiently in large regions. This provides a tool for operators to optimize the quality of water stored within surface storage ponds and increasing the readiness and availability of non-fresh water.