Due to the increasing demands of highly dense seismic networks deployed in noisy environments, it's common that both seismic networks and noise sources such as wind farms and hydrocarbon infrastructure will share locations across the United States in regions such as Oklahoma. Seismic noise sources such as wind turbines poses an interesting scenario where both natural wind source coupling and resonance frequencies of the turbine blades and towers are transmitted through the subsurface. Understanding the characteristics of the noise field associated with anthropogenic noise is important to develop better techniques in noise suppression, identify near-surface resonance, and improve signal-to-noise ratio. We investigate three spatially independent temporary nodal arrays. The first array records noise measurements of the wind and wind turbine generated noise within the seismic field through the application of the power density function and noise correlation on 3-component waveforms collected from a temporary array of 5 Hz nodes. The temporary array consists of 8 Fairfield nodes that were active for one-month with varying distances (10 m - 2000 m) from wind turbine towers located in Grant County, Oklahoma. We compare waveform signals measured from another temporally concurrent 64 Fairfield node temporary array deployed 70 km west of the Grant County array in Alfalfa County and lacks proximity to any wind turbines. The spectral amplitudes and peak frequencies of the power spectrum show spatial temporal variations in noise levels in respect to the location of the wind turbine towers. Noise amplitude decreases with distance from the wind turbine and are not detectable in Alfalfa County. We also investigate the 2016 IRIS wavefield nodal array for a larger array aperture and similar deployment location of the Grant County array. Wind speed correlates power spectrum peak frequencies observed at multiple frequencies along with a constant peak at approximately 0.27 Hz which is explained as the resonance of the wind turbine tower. Directivity is characterized using cross-correlation function where time lag indicates signal propagation. We observe the wind turbines to be a clear source of seismic noise with power degradation at distance and can better identify these signals through comparison with the distant array.