As more and more world major oil fields mature, more water begins to be produced from oil producers because of aquifer encroachment and/or water injection. Currently, it has been well known that the oil industry has to handle more produced water than oil which makes the oil industry looks more like a "water industry". How to wisely handle the tremendous amount of unwanted produced water is an imperative task that most oil companies have to face. This paper describes the development of produced water management techniques in the petroleum industry and summarizes what petroleum engineers have learnt so far. Various cases are discussed on the produced water management in the industry. The results of our study indicate if the unwanted produced water is not properly managed, it will seriously impact the economics of the project through required water treatment and disposal costs. However, the properly management of the produced water can lead to significant cost reduction and improve revenue from hydrocarbon production.

Poyang Lake is the largest freshwater lake in China, with a wide area and abundant species resources. It is a serious issue to protect and monitor the water quality of Poyang lake. This paper proposes to use principal component analysis (PCA) to evaluate the water pollution index of Poyang Lake. The input variables of PCA are the weekly monitoring water pollution factors including dissolved oxygen (DO), chemical oxygen demand (CODMn) and NH4+-N. The water quality monitoring station is in Hukou County of China from 2004 to 2014. Finally, a series of new water pollution indexes are generated by PCA to reflect the change characteristics of lake water pollution. The results can provide support for the comprehensive evaluation of lake water quality. Meanwhile, the results also discuss the variation in water pollution, which is practical and innovative.

In order to accurately quantify the terrain complexity, a simple and accurate terrain complexity assessment (TCA) model is proposed. Taking Ningdu county in Jiangxi Province of China as an example, firstly, six terrain factors (named slope, topographic relief degree, surface cutting depth, surface roughness, elevation variation coefficient and topographic factors) of Ningdu county are extracted based on the Digital Elevation Model (DEM) with 30 m resolution and ARCGIS 10.2 software. Secondly, terrain complexity indexes of Ningdu County are obtained using k-means clustering. Results show that a current and effective spatial distribution characteristic of topographic complexity in Ningdu county is produced, and the very low and low terrain complexity indexes account for 33.28%, 28.35% respectively. The terrain complexity can be evaluated effectively by k-means clustering model. The terrain complexity can be provided for environmental protection and land use planning.