3 resultados para TIME-TREND ANALYSIS
em Digital Commons - Michigan Tech
Resumo:
The number of record-breaking events expected to occur in a strictly stationary time-series depends only on the number of values in the time-series, regardless of distribution. This holds whether the events are record-breaking highs or lows and whether we count from past to present or present to past. However, these symmetries are broken in distinct ways by trends in the mean and variance. We define indices that capture this information and use them to detect weak trends from multiple time-series. Here, we use these methods to answer the following questions: (1) Is there a variability trend among globally distributed surface temperature time-series? We find a significant decreasing variability over the past century for the Global Historical Climatology Network (GHCN). This corresponds to about a 10% change in the standard deviation of inter-annual monthly mean temperature distributions. (2) How are record-breaking high and low surface temperatures in the United States affected by time period? We investigate the United States Historical Climatology Network (USHCN) and find that the ratio of record-breaking highs to lows in 2006 increases as the time-series extend further into the past. When we consider the ratio as it evolves with respect to a fixed start year, we find it is strongly correlated with the ensemble mean. We also compare the ratios for USHCN and GHCN (minus USHCN stations). We find the ratios grow monotonically in the GHCN data set, but not in the USHCN data set. (3) Do we detect either mean or variance trends in annual precipitation within the United States? We find that the total annual and monthly precipitation in the United States (USHCN) has increased over the past century. Evidence for a trend in variance is inconclusive.
Resumo:
One of the original ocean-bottom time-lapse seismic studies was performed at the Teal South oil field in the Gulf of Mexico during the late 1990’s. This work reexamines some aspects of previous work using modern analysis techniques to provide improved quantitative interpretations. Using three-dimensional volume visualization of legacy data and the two phases of post-production time-lapse data, I provide additional insight into the fluid migration pathways and the pressure communication between different reservoirs, separated by faults. This work supports a conclusion from previous studies that production from one reservoir caused regional pressure decline that in turn resulted in liberation of gas from multiple surrounding unproduced reservoirs. I also provide an explanation for unusual time-lapse changes in amplitude-versus-offset (AVO) data related to the compaction of the producing reservoir which, in turn, changed an isotropic medium to an anisotropic medium. In the first part of this work, I examine regional changes in seismic response due to the production of oil and gas from one reservoir. The previous studies primarily used two post-production ocean-bottom surveys (Phase I and Phase II), and not the legacy streamer data, due to the unavailability of legacy prestack data and very different acquisition parameters. In order to incorporate the legacy data in the present study, all three poststack data sets were cross-equalized and examined using instantaneous amplitude and energy volumes. This approach appears quite effective and helps to suppress changes unrelated to production while emphasizing those large-amplitude changes that are related to production in this noisy (by current standards) suite of data. I examine the multiple data sets first by using the instantaneous amplitude and energy attributes, and then also examine specific apparent time-lapse changes through direct comparisons of seismic traces. In so doing, I identify time-delays that, when corrected for, indicate water encroachment at the base of the producing reservoir. I also identify specific sites of leakage from various unproduced reservoirs, the result of regional pressure blowdown as explained in previous studies; those earlier studies, however, were unable to identify direct evidence of fluid movement. Of particular interest is the identification of one site where oil apparently leaked from one reservoir into a “new” reservoir that did not originally contain oil, but was ideally suited as a trap for fluids leaking from the neighboring spill-point. With continued pressure drop, oil in the new reservoir increased as more oil entered into the reservoir and expanded, liberating gas from solution. Because of the limited volume available for oil and gas in that temporary trap, oil and gas also escaped from it into the surrounding formation. I also note that some of the reservoirs demonstrate time-lapse changes only in the “gas cap” and not in the oil zone, even though gas must be coming out of solution everywhere in the reservoir. This is explained by interplay between pore-fluid modulus reduction by gas saturation decrease and dry-frame modulus increase by frame stiffening. In the second part of this work, I examine various rock-physics models in an attempt to quantitatively account for frame-stiffening that results from reduced pore-fluid pressure in the producing reservoir, searching for a model that would predict the unusual AVO features observed in the time-lapse prestack and stacked data at Teal South. While several rock-physics models are successful at predicting the time-lapse response for initial production, most fail to match the observations for continued production between Phase I and Phase II. Because the reservoir was initially overpressured and unconsolidated, reservoir compaction was likely significant, and is probably accomplished largely by uniaxial strain in the vertical direction; this implies that an anisotropic model may be required. Using Walton’s model for anisotropic unconsolidated sand, I successfully model the time-lapse changes for all phases of production. This observation may be of interest for application to other unconsolidated overpressured reservoirs under production.
Resumo:
We investigate how declines in US emissions of CO and O3 precursors have impacted the lower free troposphere over the North Atlantic. We use seasonal observations for O3 and CO from the PICO-NARE project for the period covering 2001 to 2010. Observations are used to verify model output generated by the GEOS-Chem 3-D global chemical transport model. Additional satellite data for CO from AIRS/Aqua and for O3 from TES/Aura were also used to provide additional comparisons; particularly for fall, winter, and spring when PICO-NARE coverage is sparse. We find GEOS-Chem captures the seasonal cycle for CO and O3 well compared to PICO-NARE data. For CO, GEOS-Chem is biased low, particularly in spring which is in agreement with findings from previous studies. GEOS-Chem is 24.7 +/- 5.2 ppbv (1-σ) low compared to PICO-NARE summer CO data while AIRS is 14.2 +/- 6.6 ppbv high. AIRS does not show nearly as much variation as seen with GEOS-Chem or the Pico data, and goes from being lower than PICO-NARE data in winter and spring, to higher in summer and fall. Both TES and GEOS-Chem match the seasonal ozone cycle well for all seasons when compared with observations. Model results for O3 show GEOS-Chem is 6.67 +/- 2.63 ppbv high compared to PICO-NARE summer measurements and TES was 3.91 +/- 4.2 ppbv higher. Pico data, model results, and AIRS all show declines in CO and O3 for the summer period from 2001 to 2010. Limited availability of TES data prevents us from using it in trend analysis. For summer CO Pico, GEOS-Chem, and AIRS results show declines of 1.32, 0.368, and 0.548 ppbv/year respectively. For summer O3, Pico and GEOS-Chem show declines of -0.726 and -0.583 ppbv/year respectively. In other seasons, both model and AIRS show declining CO, particularly in the fall. GEOS-Chem results show a fall decline of 0.798 ppbv/year and AIRS shows a decline of 0.8372 ppbv/year. Winter and spring CO declines are 0.393 and 0.307 for GEOS-Chem, and 0.455 and 0.566 for AIRS. GEOS-Chem shows declining O3 in other seasons as well; with fall being the season of greatest decrease and winter being the least. Model results for fall, winter, and spring are 0.856, 0.117, and 0.570 ppbv/year respectively. Given the availability of data we are most confident in summer results and thus find that summer CO and O3 have declined in lower free troposphere of the North Atlantic region of the Azores. Sensitivity studies for CO and O3 at Pico were conducted by turning off North American fossil fuel emissions in GEOS-Chem. Model results show that North America fossil fuel emissions contribute 8.57 ppbv CO and 4.03 ppbv O3 to Pico. The magnitude of modeled trends declines in all seasons without North American fossil fuel emissions except for summer CO. The increase in summer CO declines may be due to a decline of 5.24 ppbv/year trend in biomass burning emissions over the study period; this is higher than the 2.33 ppbv/year North American anthropogenic CO model decline. Winter O3 is the only season which goes from showing a negative trend to a positive trend.