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Tracer testing is a powerful tool for reservoir surveillance. Conducting and analyzing an interwell tracer test (IWTT) before starting an enhanced-oil-recovery (EOR) flood provides specific information required to balance the pattern's swept pore volume (PV) and to optimize chemical or solvent use. Tracer testing also plays an important role in EOR by establishing a baseline for estimating incremental volume swept and recovery factor. A key limitation to tracer testing is the time required to obtain a complete interpretation of the test results. Conventional interpretation methods require observing exponential decline in the tracer concentration from all producers; depending on the pattern size and processing rate, this can take many months or years. Meanwhile, the EOR flood is delayed, thereby eroding its value and reducing the remaining oil target. We have developed a method for analyzing tracer data from relatively early times that is based, in part, on a new way to extrapolate the tracer data, providing timely information to optimize flood performance. The extrapolation can be performed soon after the peak tracer concentration is observed in the well with the slowest response. We illustrate the extrapolation procedure with a synthetic, yet realistic, data set showing that the new methods result in a good approximation at much earlier times. We then compare 'early time analysis' swept PVs with the (correct) swept PVs using the complete tracer data set. We also discuss how early-time approximations can thus provide the opportunity to optimize chemical-flood performance and to enable field startup of EOR floods in a timely fashion. [ABSTRACT FROM AUTHOR]

Paratuberculosis (Johne's disease), an enteric disorder in ruminants caused by Mycobacterium avium ssp. paratuberculosis, causes economic losses in excess of $200 million annually to the US dairy industry. Costly diagnostic testing, cumbersome control programs, incurability, and ineffective vaccination all make M. avium ssp. paratuberculosis susceptibility a good candidate for genetic studies and genetic selection a potentially useful adjunct to management-based control programs. No report has been published for heritability of susceptibility to M. avium ssp. paratuberculosis infection in Jersey cattle. The objective of this study was to estimate variance components and heritability for susceptibility to M. avium ssp. paratuberculosis infection in US Jersey cattle. Data consisted of complete serum ELISA and partial fecal culture results on a total of 2,861 Jersey cows from 23 commercial herds throughout the United States after editing. Four M. avium ssp. paratuberculosis susceptibility phenotypes were defined using (1) ELISA sample-to-positive ratios as a continuous trait, (2) ELISA results as a binary trait (positive = 1, negative = 0), (3) ELISA results as an ordered categorical trait, and (4) a combined test in which ELISA and fecal culture results were both taken into account in a binary analysis. Three statistical models, including linear, binary threshold, and ordered threshold sire models, were used to analyze the data. All analyses were executed using the restricted maximum likelihood method in AS-Reml 3 software. The heritability estimates were low to moderate and ranged from 0.08 (±0.03) to 0.27 (±0.11) based on different trait definitions. The nonzero heritability indicates that susceptibility to M. avium ssp. paratuberculosis infection in Jersey cattle is influenced by genetic factors. Therefore, selection of the least susceptible animals could decrease genetic predisposition to M. avium ssp. paratuberculosis infection in Jersey populations in future generations. [ABSTRACT FROM AUTHOR]

Enhanced oil recovery (EOR) by surfactant flooding is the key to unlocking the next billion barrels of oil for Minas, one of the world's largest waterflood fields. An interwell tracer test (ITT-1) was performed before a surfactant field trial (SFT) to ensure well injectivity, demonstrate pattern confinement, quantitatively describe interwell connectivity and sweep efficiency, and provide sufficient data for reservoir evaluation. The tracer test was designed by numerical simulation. The test started in November 2009 and was terminated in February 2010. Analytical interpretation based on moment analysis and numerical reservoir simulations was conducted to evaluate ITT-1 results. Interpretation of the test results indicated various operational and reservoir properties that would have likely led to failure of the surfactant pilot. Hydraulic control of the SFT pattern was not achieved; in fact, less than 20% of one tracer was recovered. Many small-scale heterogeneities were identified that led to a lower-than-expected reservoir volume contacted. Unexpected communication between the target sand and the underlying sands outside the pattern also contributed to low tracer recovery and low swept volume. The tracer test was history matched, and additional features were incorporated in the reservoir model, and a new tracer design (ITT-2) was optimized to correct low sweep efficiency and poor hydraulic control. New information from ITT-2 will be used to further optimize operating conditions for SFTs. Failure to conduct the tracer tests would have likely revealed these unfavorable reservoir and operational conditions during the SFT. Had oil recovery been poor (because of low swept volume), it would have erroneously been attributed to a poor SFT rather than to the true causes. ITT-1 is considered successful because it allowed us to redesign injection/hydraulic control during the relatively inexpensive tracer test and thus evaluate the surfactant trial without bias. [ABSTRACT FROM AUTHOR]

The objectives were to estimate heritabilities and genetic variances for anovulation at ∼50 d in milk and pregnancy loss occurring between first and second pregnancy diagnoses after artificial insemination. Data were originally collected for trials on reproductive management. Anovulation data consisted of 5,818 records from 13 studies in 8 herds with an overall prevalence of 23.3%. A Bayesian approach using Markov Chain Monte Carlo methods was used in mixed threshold models for both traits. The statistical model for anovulation included fixed effects [parity, herd-study-treatment, and body condition score (BCS)], covariates (inbreeding and milk yield), and random effects (sire and residual). A second statistical model included all terms in the first model except BCS. In addition, 2 bivariate, mixed sire models were used to analyze anovulation with BCS and anovulation with milk yield. The posterior mean heritability estimate for anovulation was 0.171 [posterior standard deviation (PSD) = 0.052]. Correlations of anovulation with milk yield were as follows: genetic = 0.168, PSD = 0.187; residual = -0.046, PSD = 0.022; and phenotypic = -0.036. Bivariate analysis of BCS with anovulation showed a genetic correlation (-0.301, PSD = 0.177) and phenotypic correlation (-0.192, PSD = 0.019). Pregnancy-loss data consisted of 3,775 records from 14 studies in 8 herds with an overall prevalence of 14.4%. Analysis of pregnancy loss used a sire-maternal grandsire threshold model with embryo survival as the subject of analysis. Independent variables consisted of fixed effects (parity and herd-study), covariates (embryo and maternal inbreeding), and random effects (sire of embryo, maternal grandsire of embryo, and residual). In addition, separate sire models were analyzed using embryo as the subject and cow as the subject of analysis. The sire-maternal grandsire model yielded a heritability for direct effect of 0.489 (PSD = 0.221) and for maternal effects of 0.166 (PSD = 0.113). In this study, the breeding value variance for embryo effects was 3 times the breeding value variance for maternal effects, indicating that, at the level of breeding values, the embryo's ability to survive has a greater effect on pregnancy loss than does the cow's ability to maintain the pregnancy. These results suggest that genetic improvement of reproductive performance could be enhanced by selection for fundamental measures such as abnormally long periods of postpartum anovulation and pregnancy loss. Larger studies of these traits are needed to obtain parameter estimates with greater precision. [ABSTRACT FROM AUTHOR]

Substantial increases of 3,500 kg of milk, 130 kg of fat, and 100 kg of protein per cow per lactation have resulted from improvements in genetics, nutrition, and management during the past 20 yr. At the same time, the interval from calving to conception increased (unfavorable) by 24 d. Genetics has accounted far about 55% of gains in the yield traits and about one-third of the change in interval to conception. Genetic gains in the yield traits and productive life have accumulated to around 1.7 and 1.2 genetic standard deviations since 1980. Unfavorable genetic changes in conception interval since 1980 and somatic cell score since 1990 have accumulated to 1.0 and 0.12 genetic standard deviations. The most important advance in selection indexes has been the introduction of nonyield traits. Advances in selection indexes have gone hand in hand with advances in data collection and genetic evaluation. As new traits were recorded in dairy management databases and as genetic evaluations were developed for these traits, they were incorporated into selection indexes. Until 1994, when somatic cell score and productive life were introduced, selection indexes provided by USDA included only yield traits. In 2000, composite type indexes for udder, feet and legs, and body size were added. Daughter pregnancy rate and service sire- and daughter-calving ease were included in 2003. The lifetime merit indexes introduced in 2003 have, for the first time, resulted in theoretical selection responses in the desired direction for all traits. During this time, the percentage relative economic weights in selection indexes increased from 0 to 45% for the nonyield traits. Selection emphasis on nonyield traits should continue to increase as additional traits (e.g., calf survival, metabolic disease, and male fertility) are introduced in the future. Wide variation exists among countries in traits included in selection indexes and in relative economic weights. Molecular genetic studies have identified many chromosome regions with potentially important major genes for economic traits. Use of DNA markers for genetic improvement is currently limited by lack of precision in marker location. Discovery of major genes will be accelerated by the availability of the bovine genome sequence, comparative genome maps and genome sequences across species, and increased use of breed crosses in molecular studies. As major genes are identified, their effects will be incorporated into genetic evaluations and selection indexes. [ABSTRACT FROM AUTHOR]

Genetic evaluation and selection is one strategy for improving female reproductive performance. Many producers use synchronization of ovulation or estrus to manage reproduction. The objective of this study was to examine the effects of reproductive synchronization on genetic parameter estimates of days to first breeding (DFB), days open (DO), and pregnancy rate at 120 d postpartum (PR120). Data were collected from 64 producers participating in an artificial insemination progeny testing program and using Dairy Comp 305 herd management software to record reproductive treatments and events. Data included 18,359 records for DFB and 16,379 records for DO and PR120. Synchronization was classified by breeding codes at time of insemination. The traits DFB and DO were analyzed using a linear model with age at calving, herd-year-season, and parity as fixed effects and sire and residual as random effects. For PR120, a threshold sire model was used with fixed effects as in the DFB and DO models. Three models were applied to the complete data sets of all traits; a base model with no synchronization effect, an expanded model with a fixed synchronization effect, and an interaction model with a random sire by herd management interaction. Herd management categories were based on an individual herd's use of synchronization protocols. Also, data subsets were analyzed separately based on cow synchronization treatment and herd management categories. Synchronized records for DFB had on average 40% higher sire variance and 60% lower residual variance than nonsynchronized records. Heritability for DFB ranged from 0.01 to 0.09. Sire variance was 40% lower for DO and 25% lower for PR120 in first synchronized records than either later-synchronized or nonsynchronized records. Residual variances for DO varied by 3% among cow treatment categories and 14% for herd management categories. Heritabilities ranged from 0.03 to 0.07 for DO and 0.10 to 0.26 for PR120. Including a fixed effect for synchr. [ABSTRACT FROM AUTHOR]