FIFE Field Research Articles

Complementary relationships for near-instantaneous evaporation

The complementary relationship between actual and potential evaporation provides evaporation (i.e. evapotranspiration) estimates from minimal data. Some versions that require a land surface temperature instead of a humidity measurement could potentially be used with routine remotely sensed surface temperature data. A comparison of alternative complementary approaches, including those that require land surface temperatures, was made at small (10–30 min) time scales with point measurements spatially, using data from the FIFE, CASES, SGP, and Sahel field experiments. The advection-aridity version and a related version based on the Penman and the Priestley–Taylor equations performed the best overall. One of the four versions that incorporated land surface temperature performed fairly well. The complementary approach appears to remain viable, especially in remote sensing applications with sparse data.

The Fife and Fergus Fields, Block 31/26a, UK North Sea

Abstract The Fife Field and its smaller satellite the Fergus Field are the southernmost of the cluster of oil fields within the UK Central North Sea. The Fife Field lies at the intersection of four blocks, 31/26a, 31/27a, 39/la and 39/2a. It is a small to moderate size offshore field with reserves of 48.3 MMSTB and is produced by five sub-sea wells through a Floating, Production, Storage, Offloading (FPSO) vessel. The field was discovered in 1991 and the first oil was produced in 1995. The Fergus Field, located in Block 39/2a, is a satellite located 5 km SE of the Fife Field. It is produced by a single well tied-back by a sub-sea flowline to the Fife Field infrastructure. The Fergus Field was discovered in 1994 and first oil was produced in 1996. Reserves are estimated as 11.3 MMSTB The main reservoir interval in both fields comprises fine-grained, heavily bioturbated, shallow marine shelf sandstones of Upper Jurassic age. Significant volumes of chert and carbonate cements, both banded and nodular, occlude porosity and impart reservoir layering within an otherwise thick sandy, mud deficient reservoir interval. Sandstone porosity is in the range 19-31%. Permeabilities are low in the Fife Field reservoir sandstones, typically less than lOOmD. By contrast, better permeabilities (average 500 mD) are seen in the Fergus Field, where a more proximal shelf sandstone facies is present within the oil leg. Two thin intervals of pebbly, very coarse-grained sandstone are intercalated with the shelf sandstones in the crest of the Fife Field. These may represent submarine toes of fan deltas sourced from an active fault system located to the north of the field. The pebbly sandstones show permeabilities in excess of a Darcy and have caused early water breakthrough problems in production wells A subsidiary reservoir is present within the Tor Formation of the Chalk Group in the Fife Field, but is not oil bearing within the Fergus Field. This comprises white to grey, intensely bioturbated, stylolitized chalk with an average porosity of 24.5% and an average air permeability of slightly less than a millidarcy. Both the Fife and Fergus Fields are defined by simple four-way dip closure at top Jurassic. An episode of structural inversion at the end of the Jurassic created both structures. The overlying Chalk oil pool in the Fife Field has a trap defined by dip closure on three sides and a probable diagenetic trapping element to the south

Rejuvenation of a Mature Asset

This article is a synopsis of paper SPE 71846, "Fife Field U.K. - Rejuvenation of a Mature Asset," by K.R. Bush, SPE, J. Wakefield, SPE, M. Shepherd, and K. Beattie, Amerada Hess Ltd., originally presented at the 2001 Offshore Europe Conference, Aberdeen, 4-7 September.

A generalized algorithm for retrieving cloudy sky skin temperature from satellite thermal infrared radiances

A physical algorithm for calculating cloudy pixel skin temperature from its neighboring clear pixels is proposed generalizing that of Jin [2000]. Two neighboring pixels over the same land cover have a difference in temperature largely explained by surface insolation. Hence this algorithm starts from the surface energy balance equation (SEB) and expresses each energy term of SEB as a function of skin temperature. Then SEB is solved to derive cloudy pixel skin temperature from neighboring clear skin temperature plus a correction term determined by surface insolation, air temperature, and wind speed. This algorithm can be used for nights and winter hemisphere high latitudes where there is no surface insolation and is applicable to any surface where the principle of SEB is applicable. The algorithm is evaluated by using FIFE and BOREAS field experiments. Its global application has been examined through simulations with the NCAR Community Climate Model (CCM) coupled with the Biosphere‐Atmosphere Transfer Scheme (BATS) simulations. The accuracy of the algorithm is encouraging: the rms error at a monthly pixel level is 1–2 K. Observed errors are greater when there is precipitation.

Remote sensing of parameters that regulate energy and water transfer at the land-atmosphere interface

The exchange of energy and water between the land surface and the atmosphere is dominated by two parameters: the fractional green vegetation cover, and the wetness of the bare soil patches. An account is given of the way satellite remote sensing can be employed to infer these parameters, and of their integration into a land surface model to simulate the surface energy and water balance. Fractional green vegetation cover is obtained by means of the AVHRR Normalized Difference Vegetation Index, adopting a simple linear relation between this vegetation index and fractional green vegetation cover. Soil moisture is retrieved using the SSM/I Polarization Difference Temperature, employing the dependence of the dielectric constant of the soil on water content. A demonstration is given of the implementation of these two parameters in a land surface model, running the latter for the temperate grassland area of the FIFE field experiment for a two-week period in summer. A comparison with observations shows that the error on the simulated energetic fluxes is of the same order as the estimated experimental error of ground-based flux measurements.

The reservoir development of the Fife Field

The Fife Field, located in the southern part of the Central North Sea. produced first oil in August 1995 after a fast-track appraisal and development programme. At that time it was predicted to contain 120 × 10 6 BBL STOIIP in a predominantly fine-grained sandstone of Volgian age of which an estimated 50 × 10 6 BBL was recoverable over a 4 year field life. Rapid water breakthrough and a fast water-cut rise in the first three production wells, all located crestally on the field, led to significant reappraisal and remodelling of the field. This paper describes the initial field development, gives an account of the work which followed the start-up of the field, and accounts for the early water breakthrough.

Interpolation of surface radiative temperature measured from polar orbiting satellites to a diurnal cycle: 1. Without clouds

The land surface skin temperature diurnal cycle (LSTD) is an important element of the climate system. This variable, however, cannot be directly obtained globally from polar orbiting satellites because such satellites only pass a given area twice per day and because their infrared channels cannot observe the surface when the sky is cloudy. To obtain the skin temperature diurnal cycle and fully utilize satellite measurements, we have designed an efficient algorithm that combines model results with satellite and surface‐based observations and interpolates satellite twice‐daily observations into the diurnal cycle. Climatological information from a climate model, CCM3/BATS, is used to determine a normalized shape (typical pattern) of the diurnal temperature for different latitudes, seasons, and vegetation types. The satellite observations, which are by themselves inadequate, are combined with the normalized modeled diurnal typical patterns to obtain the skin temperature diurnal cycle. The normalized typical patterns depend on the parameters of the diurnal insolation, such as sunrise, sunset, and peak times, and are also affected by the type of vegetation cover and soil moisture. The underlying physical foundation of this algorithm is that the diurnal cycle of temperature can be viewed as a composite of a daily average, diurnal periodic component, and random aperiodic component (noise). With the assumption that the noise can be ignored, the daily average can be inferred from satellite twice‐per‐day measurements and the periodic part can be obtained from modeled climatologies, providing a reasonable approach for estimation of the diurnal cycle of skin temperature. The general framework of the algorithm and its application for the clear‐sky (cloud free) conditions are presented. This cloud‐free version of algorithm is evaluated using FIFE and BOREAS field experiment surface observations. Regional tests over the Mississippi River basin have also been conducted using GOES‐8 and AVHRR observations. Uncertainties of this cloud‐free algorithm have been analyzed, indicating an accuracy of about 1–2 K for monthly cloud‐free diurnal cycles at near‐pixel resolution.

Impact of soil heterogeneity in a mixed-layer model of the planetary boundary layer

The dynamics of soil moisture and temperature states are forced by land surface fluxes that form the coupling between the soil and the atmosphere. This two-way interaction between the soil and the atmosphere results in feedback mechanisms that affect the temporal patterns of variability of the system. To understand these characteristics of soil moisture and temperature variability, a one-dimensional coupled mixed-layer model of the land surface and the planetary boundary layer energy and humidity budgets is constructed. To allow integrations on the order of days, the model includes both the growth phase and the collapse phase of mixed layer evolution. The model includes the radiative effects due to the presence of clouds. Given the incoming shortwave radiation, lapse rates of temperature and humidity above the mixed layer and lateral windspeed, the model predicts all longwave radiative and turbulent surface heat fluxes. The model is shown to capture accurately observations taken during the FIFE field experiment. With this model, the impact of soil heterogeneity on the evolution of the surface and mixed-layer energy and humidity budgets is examined, using hydraulic properties from sand, loam and clay soils. It is assumed that the small correlation length scale of soil hydraulic properties and surface inhomogeneities are averaged out in the mixed layer. Relative to a uniform soil, heterogeneity increases the spatial mean latent heat flux for conductive soils and decreases it for unconductive soils, due to decreased and increased percolation respectively. Locally decreasing latent heat fluxes cause a warmer and drier mixed layer and through that an increase of the latent heat flux over other areas. This mixed-layer feedback reduces the impact of heterogeneous surface fluxes.

Feedbacks in the Land-Surface and Mixed-Layer Energy Budgets

A mixed-layer model of the surface energy budget and the planetary boundary layer (PBL) is developed, based on the prognostic equations for soil temperature, mixed layer potential temperature and specific humidity and the growth and abrupt collapse of the PBL. Detailed parameterizations of the longwave radiative fluxes are included. The feedbacks in the uncoupled (i.e. surface energy budget with non-responding PBL) and coupled land surface and atmospheric mixed-layer energy budgets are examined. A simplified, time continuous, version of the model, in which the specific humidity budget is the balance of evapotranspiration and dry-air entrainment, and the PBL height is given by the lifted condensation level, is shown to be in good agreement with the complete model. By forcing the simplified model with daily mean rather than periodic solar radiation, an equilibrium model state is achieved where the fluxes are in close agreement with the daily mean fluxes corresponding to the periodic forcing. The model also agrees favorably with measurements from the FIFE field experiment. Feedbacks are examined using the equilibrium model state. The uncoupled and coupled model sensitivities with respect to the minimal stomatal resistance and the atmospheric specific humidity not only differ in magnitude, but in sign as well. This results puts into question the extent to which uncoupled land-surface models that are forced with atmospheric variables may be used in sensitivity studies.

Mesoscale fluxes over heterogeneous flat landscapes for use in larger scale models

We have developed a framework to parameterize mesoscale fluxes of heat, moisture, and momentum, in a cloud-free environment, which result from heterogeneous heating of flat land surfaces. The importance and parameterizability of these mesoscale fluxes is demonstrated using the mathematical concept of predictability. This methodology is used to estimate the relative importance of mesoscale, as contrasted with turbulent fluxes, in the Konza Prairie of Kansas during the FIFE field experiment.

The Fife Field, UK central North Sea

The Fife Field is located in the far southeastern part of the Central North Sea Basin close to the UK, Norwegian, Danish median line. The field is a shallow relief four-way dip closure formed by inversion during Late Cretaceous/ early Tertiary times. The reservoir consists of thick Upper Jurassic, heavily bioturbated sandstones which are considered to have been deposited in a similar setting to the Fulmar Formation. The depth to the top of the Upper Jurassic at the crest of the field is 8250 ft sub-sea with the oil-water contact at 8512 ft sub-sea. The seal to reservoir is provided by Volgian-Ryazanian shales of the Kimmeridge Clay Formation and Upper Cretaceous Chalk. Although Jurassic sandstones form the primary reservoir, additional hydrocarbons have been encountered in the Tor Formation of the Chalk Group which is fractured over the crest of the field. The Fife Field was discovered in 1991 and is currently under development. Production started in August 1995 via the 'Uisge Gorm' Floating Production Storage and Offloading facility (FPSO). STOIIP is estimated at 132 x 106BBL and ultimate recovery is predicted to be 34 x 106 BBL oil. The low mobility of the oil and the low vertical permeability of the reservoir contribute to the predicted low (26%) recovery efficiencies.