Context The ability to accurately estimate age of animals is important for both research and management. The two methods for age estimation in ungulates are tooth replacement and wear (TRW) and cementum annuli (CA). Errors in estimated TRW ages are commonly attributed to environmental conditions; however, the influence of environmental variables on tooth wear has not been quantified. Further, the performance of CA in environments with weak seasonality has not been thoroughly evaluated. Aims The study had the following three goals: identify environmental and morphological factors that influenced estimated ages, quantify accuracy of TRW and CA, and develop TRW ageing criteria that minimise error. Methods We used data from harvested (n = 5117) and free-ranging, known-age white-tailed deer (n = 134) collected in southern Texas, USA, to quantify environmental and morphological influences on estimated TRW ages, and assess biases in both methods. Key results We observed substantial variation in age estimates for both TRW and CA. Soil, drought and supplemental nutrition had minor effects on tooth wear, insufficient to alter age estimates by ≥1 year. Body mass and antler size influenced age estimates for TRW only for extreme outliers. Both methods were biased and tended to under-estimate ages of adult deer, especially TRW. Wear on the first molar was most correlated with the known age (r2 = 0.78) and allowed biologists to correctly place known-age deer into age classes of 2, 3–5, and ≥6 years old 72%, 73% and 68% of the time, an improvement compared with the 79%, 48% and 28% accuracy from pooled TRW. Conclusions We observed substantial inter- and intra-individual variation in tooth-wear patterns that became more pronounced in older deer. Individual variation had a greater influence on TRW ages than did environmental covariates, whereas CA ages appeared unaffected by environment. Although variable, age estimates were ±1 year of the true age 87% and 93% of the time for TRW and CA respectively. Implications Managers, ecologists and epidemiologists often incorporate ages into population models. The high inter-individual variation in estimated ages, the tendency to underestimate ages of older deer, and the ageing method need to be considered.

Permeability heterogeneity is a well known feature that is present in most if not all reservoirs. Initially when the reservoir is in hydrostatic equilibrium the differences in permeability within the same reservoir unit do not manifest. However as soon as production starts and a pressure drawdown is introduced to the system fluids will start moving towards the wellbore following the easiest paths within the rock. Therefore a system of "flowing units" develops with time allowing the zones with relative high permeability to produce faster than the relatively low permeability zones. When a well is completed and perforated it is good practice to evaluate reservoir properties and well performance by carrying out transient well testing and multirate tests. Well test interpretation gives a good estimation of kh, skin and boundary effects. Multirate tests, particularly important in gas wells and high flowrate oil wells, allow evaluation of well deliverability and non-Darcy effects. It is therefore important to define the correct thickness that is actively contributing to flow. The effective thickness will be the sum of all the high permeability flowing units. In fact, and depending on the permeability contrast, the few most permeable units are responsible for most of production. Production Logging can verify and quantify flow contribution from these intervals. Differential depletion within this interbedded layered system occurs by stages. Initially the zones with the highest permeabilities will produce faster and drain their connected volume until a differential pressure threshold is reached and crossflow from the surrounding poorer-quality reservoir facies starts. A production logging survey is a snapshot of the flowing profile across the producing intervals at that particular point in time. In order to monitor this dynamic behaviour running production logging surveys at different times during the field's life is highly recommended especially in mature fields that produce from layered systems or interbedded units within the same formation. Time-lapse production logging provides a realistic visualization of flowing behaviour and helps pre-development of a production optimisation strategy focused in maximizing reserve recovery. The previous statements are supported by field examples where this pattern of permeability zonation has been observed over time. Introduction The term Flow Unit has been used originally to describe the correlateable units in reservoirs1.Hydraulic Flow Units were later introduced to cluster core plugs with similar petrophysical properties2. The Stratigraphically-Modified Lorenz Plot has been used more recently to identify Flow Units3 in the sense of ‘flowing units’ identified by the production log.The term Flow Unit means different things to different people so we use the term "flowing units" in this paper to define the units detected by production logs to be flowing. This paper investigates the evolution of these flowing units over production time in a well-layered system with crossflow. The paper shows the link between evolution of flowing units with time and initial evaluation measures. Laterally continuous, multilayered reservoirs with high permeability contrast between layers with crossflow behaviour have a distinctive long-term production behaviour. Preferential depletion develops over time and the most permeable and consequently the most productive intervals act like "fracture channel" systems collecting the produced fluids from the surrounding less permeable units and carrying them to the wellbore.These reservoirs are called double porosity, but as this terminology is often associated with naturally-fractured reservoirs we call these double matrix porosity.In well testing these reservoirs are also called dual permeability. The most common way of quantifying the production profile along the perforated section in a well is to run a production logging survey. Time-lapse production logging suggests a monitoring plan of evaluating well's production profile at different points in time, which is considered fundamental in understanding production dynamics and production optimisation.

An Ecuadorian lease ("Bloque 61") composed of 14 oil fields represents the most productive asset in the country. It contains 5.3 billion barrels of original oil in place (OOIP) distributed in four complex producing reservoirs. After 44 years of production and with a decline rate of 31% per year, maintaining the production from these fields represents an important challenge from the subsurface and execution viewpoints. In December 2015, an integrated service contract was signed with the national oil company (NOC) with a fixed investment for the development of the entire lease. The challenge of the project was to maximize the value of a depleted asset through the framework of the contract. This mature asset has many opportunities to boost production and reserves by implementing an aggressive fit-for purpose development. The opportunities screened and implemented in only 12 months consisted of reaching new oil in appraisal and exploration areas and redevelopment of mature zones with horizontal and infill drilling with mainly reentry wells. Most valuable of all was the implementation of six waterflooding projects. All of these were executed in the Amazon rainforest where there is a pressing need to reduce environmental and social impact. This exploitation philosophy has successfully changed the asset’s production decline, ramping production up from 60,000 BOPD to 80,000 BOPD. This integrated field development plan has amalgamated several technologies with a specific objective of optimizing the value of the asset. The long term was assessed through the drilling of exploration and appraisal opportunities where prospective resources were recategorized to reserves. The medium term was tackled by drilling horizontal wells and re-entries to optimize sweep efficiency and implementing water injection in the main structures. The short term was directed by executing workovers in areas where the water injection was in place. The asset value was recovered and increased as shown by a reserve’s replacement ratio of 1.13. This approach will serve as a framework for the future integrated development of these types of mature assets. The technologies implemented have helped accelerating and optimizing the conceptualization and execution of the project; a few of these include high-resolution reservoir simulation, dumpflooding, closed-loop water source system, and dual-string completions. The integration of strong domain expertise, coupled with advanced technologies and workflows, has led to outstanding results.

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The Shushufindi-Aguarico field (SSFD), located in the Oriente basin of Ecuador, has been under production since1972. In December 2011, when Consorcio Shushufindi (CSSFD) joined efforts with the national oil company PetroAmazonas EP (PAM), there were about 150 wells in the field with a production of 45,000 BOPD. Since then, 109 new wells and 91workovers have been completed in the field, raising the production to 80,000 BOPD by August 2016. Reservoir characterization of the SSFD field was undertaken with sequential objectives in mind. First, to answer the project needs for primary recovery, the effort focused on the main reservoirs (Lower U and Lower T) to create the annual work plans for the initial years of the project. Thereafter, a more refined petrophysical analysis, production data re-evaluation, and individual well diagnosis for water production provided the necessary characterization results for the field development plan (FDP) with a thorough mapping of the hydraulic units (HUs). In Shushufindi-Aguarico field, stratigraphic compartmentalization occurs when flow is prevented across sealed boundaries within the reservoir. These boundaries are caused by a variety of geological and dynamic factors. The characterization of the heterogeneity in the U and T reservoirs was a key starting point in understanding how lithology controls the horizontal and vertical movement of fluids, the reservoir depletion mechanisms, and the different completion options for a specific well.