The issue of pipeline scaling and oil-water separation caused by treating produced water in Alkali/Surfactant/Polymer (ASP) flooding greatly limits the wide use of ASP flooding technology. Therefore, this study of the demulsification-flocculation mechanism of oil-water emulsion in ASP flooding produced water is of great importance for ASP produced water treatment and its application. In this paper, the demulsification-flocculation mechanism of produced water is studied by simulating the changes in oil-water interfacial tension, Zeta potential and the size of oil droplets of produced water with an added demulsifier or flocculent by laboratory experiments. The results show that the demulsifier molecules can be adsorbed onto the oil droplets and replace the surfactant absorbed on the surface of oil droplets, reducing interfacial tension and weakening interfacial film strength, resulting in decreased stability of the oil droplets. The demulsifier can also neutralize the negative charge on the surface of oil droplets and reduce the electrostatic repulsion between them which will be beneficial for the accumulation of oil droplets. The flocculent after demulsification of oil droplets by charge neutralization, adsorption bridging, and sweeping all functions together. Thus, the oil droplets form aggregates and the synthetic action by the demulsifier and the flocculent causes the oil drop film to break up and oil droplet coalescence occurs to separate oil water.

Conversion from very inert nitrogen to ammonia is crucial to the industrial production of fertilizers and other fundamental chemicals. To predict the possible reaction pathways and barriers of the nitrogen reduction reaction (NRR) in metal-zeolites, we set up a dataset consisting of electronic structures and reaction energies for 492 metal-zeolite structures with 27 metal elements (including 3d, 4d, and 5d transition metal and main group Pb and Bi metal atoms). The important role of hydrogen bonding (HB) interaction in facilitating the hydrogenation step (N₂* → NNH*) but disfavoring the dehydrogenation step (NNH₃* → N*) of the NRR is revealed by using a graph convolutional neural network (GCNN) model with the multilevel attention mechanism. A local acidity (LA) descriptor is defined by the combination of the electronegativity, first ionization energy, and atom radius of the embedded metal in various substrates (including zeolites, 2D materials, etc.), from which good predictivity of reaction energies was gained by using explainable machine learning (ML) models (e.g., XGBoost: R² = 0.84) with an addition of geometry distortion and charge transfer descriptors along reaction pathways. The pathway probability of distal, alternating, and enzymatic processes is also predicted from the geometry and charge features with satisfactory performance. The promising zeolites with embedded Ti, Co and Nb atoms were recommended to favor the NRR with lower energy inputs of 0.13, 0.04, and 0.54 eV. For experimentally synthesized photocatalytic Ti-exchanged zeolites, the ML predicted maximum energy inputs are decreased with decreasing LA values, in line with the increased ammonia yield from 4A, 3A, to 5A of pore sizes. The predictive model for energy and pathway prediction and the LA descriptor could also be transferred to metal decorated 2D materials and non-metal B-containing systems.

Previous studies showed the difficulty during polymer flooding and the low producing degree for the low permeability layer. To solve the problem, Daqing, the first oil company, puts forward the polymer-separate-layer-injection-technology which separates mass and pressure in a single pipe. This technology mainly increases the control range of injection pressure of fluid by using the annular de-pressure tool, and reasonably distributes the molecular weight of the polymer injected into the thin and poor layers through the shearing of the different-medium-injection-tools. This occurs, in order to take advantage of the shearing thinning property of polymer solution and avoid the energy loss caused by the turbulent flow of polymer solution due to excessive injection rate in different injection tools. Combining rheological property of polymer and local perturbation theory, a rheological model of polymer solution in different-medium-injection-tools is derived and the maximum injection velocity is determined. The ranges of polymer viscosity in different injection tools are mainly determined by the structures of the different injection tools. However, the value of polymer viscosity is mainly determined by the concentration of polymer solution. So, the relation between the molecular weight of polymer and the permeability of layers should be firstly determined, and then the structural parameter combination of the different-medium-injection-tool should be optimized. The results of the study are important for regulating polymer injection parameters in the oilfield which enhances the oil recovery with reduced the cost.

The water produced by alkaline–surfactant–polymer (ASP) flooding is difficult to treat due to the presence of residual chemicals. Therefore, research and development of efficient and low-cost methods for the treatment of ASP flooding produced water is necessary. Chemical destabilization is the most common and effective way to treat the produced water. This paper describes an optimization method for demulsification and flocculation. Some demulsifiers and flocculants commonly used in oilfields were screened, compounded, and optimized. Since the effect of treatment using only demulsifier or flocculant to treat the produced water is often not enough to meet the reinjection standard, an orthogonal experiment was carried out to study the demulsification–flocculation method to treat produced water. Five main influencing factors of the oil concentration were investigated. Based on the results of the range analysis and the relationship between the five factors and oil concentration, the order of significant factors was found to be demulsifier dosage > flocculant dosage > settling time > stirring time > stirring intensity, and the optimal demulsification–flocculation treatment conditions were successfully optimized.

In order to study the distribution and flow pattern of foam in the wellbore during the process of foam drainage and gas recovery, A coupled model of gas and foam flow in wellbore was established. The distribution characteristics of foam in the wellbore during the process of foam drainage and gas recovery were analyzed through experiments. The concept of foaming efficiency and bubble carrying efficiency were introduced, and the drainage time and liquid accumulation time of foam drainage gas recovery in wellbore were calculated. The research results show that: In the process of foam drainage, there are two states of heterogeneous foam flow and homogeneous foam flow in the wellbore. Under the influence of the high flow rate of natural gas in the wellbore, the migration rate of bubbles near the wellbore is slow. High gas yield and low bubble density are beneficial to the rapid initiation of foam. Due to the double influence of gas carrying force and gravity, bubbles will show relatively complex motion characteristics, and the fluid level height in the wellbore is linearly related to time under different influencing factors in the process of gas well drainage. The research in this article is of great significance for precise drainage of foam drainage gas recovery. Graphical Abstract