The Gullfaks A platform is among the facilities included in the contracts. Two Norwegian well-intervention specialists, Altus Intervention AS and Archer Integrated Services AS have been awarded framework contracts for supplying integrated wireline services for well intervention to Equinor’s fixed platforms. The estimated total value of the contracts is close to $120 million per year. The 5-year agreement, beginning in May, includes the provision of fully integrated intervention services including cased-hole mechanical wireline services, tractor and powered mechanical services, and electric-line logging services on a total of 22 installations. Focus areas will include use of technology and digital solutions, emission reductions, operational cost savings, and potentially remote operations by moving personnel from offshore to onshore locations.

This page provides an overview of Pulsed-Neutron-Lifetime (PNL) devices and their applications. They probe the formation with neutrons but detect gamma rays. Chlorine has a particularly large capture cross section for thermal neutrons. If the chlorine in the formation brine dominates the total neutron capture losses, a neutron-lifetime log will track chlorine concentration and, thus, the bulk volume of water in the formation. For constant porosity, the log will track water saturation, Sw.

The latitude/longitude mapping system is widely used worldwide, except in the United States. This approach is more orderly and easily allows the wells to be located in relation to other known wells or landmarks. The "lat/long" system is now being introduced in the United States in conjunction with the township/range scheme. Selecting offset wells to be used in data collection is important. Using Figure 1 as an example, assume that a 13,000-ft prospect is to be drilled in the northeast corner of Section 30, T18S, R15E. The best candidates for offset analyses are shown in Table 1. Although these wells were selected for control analysis, available data from any well in the area should be analyzed.

Many approaches to estimating permeability exist. Recognizing the importance of rock type, various petrophysical (grain size, surface area, and pore size) models have been developed. This page explores techniques for applying well logs and other data to the problem of predicting permeability [k or log(k)] in uncored wells. If the rock formation of interest has a fairly uniform grain composition and a common diagenetic history, then log(k)-Φ patterns are simple, straightforward statistical prediction techniques can be used, and reservoir zonation is not required. However, if a field encompasses several lithologies, perhaps with varying diagenetic imprints resulting from varying mineral composition and fluid flow histories, then the log(k)-Φ patterns are scattered, and reservoir zonation is required before predictive techniques can be applied.

Estimating permeability has been approached using a variety of models considering different rock characteristics. Two ideas inherent in Kozeny-Carman are important for later developments: the dependence of k on a power of porosity and on the inverse square of surface area. The various forms of Eq. 1 have been used as a starting point for predicting permeability from well log data by assuming that residual water saturation is proportional to specific surface area, Σ. Specific surface as ratio of pore surface area to rock volume: ....................(1b) Granberry and Keelan[1] published a set of curves relating permeability, porosity, and "critical water" saturation (Sciw) for Gulf Coast Tertiary sands that frequently are poorly consolidated. Their chart, originally presented with Sciw as a function of permeability with porosity as a parameter, is transposed into log(k)-Φ coordinates in Figure 1. The Sciw parameter is taken from the "knee" of a capillary pressure curve and is greater than irreducible water saturation, Swi.

Several models have been devised to accommodate the influence of mineralogical textures on permeability (k). The first two described below are based on the Kozeny-Carman equation; the third uses a network topology that is independent. Herron[1] uses Kozeny-Carman's equation where surface area is defined as the ratio of pore surface area to grain volume as a starting point for a model using mineralogical abundances in place of specific surface area. Mineral abundances are obtained by performing an element-to-mineral transform on data from a logging tool that measures chemical elemental concentrations by means of neutron-induced gamma ray spectroscopy. The coefficient Af is a textural maturity indicator; it can be used to reflect the amount of feldspar alteration to clay minerals.

Density logging is another application of gamma rays in gathering data about subsurface formations. Density logging tools rely on gamma-gamma scattering or on photoelectric (PE) absorption. A density-logging tool sends gamma rays into a formation and detects those that are scattered back. Typical logging sondes use a Cesium-137 source, which emits gamma rays of 0.66MeV. At this high energy level, Compton scattering dominates.

Acoustic logging tools can assist in evaluating porosity because the compressional velocity of sound in fluid is less than the velocity in rock. If there is pore space in the rock, and it is fluid-filled, the acoustic energy will take longer to get from the transmitter to the receiver (i.e., low velocity indicates high porosity). These factors are related through an empirical relationship known as the Wyllie time-average equation.[2] When the velocity (transit time, Δt, or travel time, t) of the rock matrix and borehole fluids are known, porosity can be computed the following ways (Eq. 1 to Eq. 4). Fluid type becomes more of a concern when oil-based mud (OBM) is used if the formation of interest is not invaded or if invasion is very shallow.

Evaluating porosity is an important petrophysical task as part of formation evaluation. This article provides an overview of techniques used in determining porosity by nuclear magnetic resonance (NMR) logging techniques. The initial amplitude of the spin-echo train is proportional to the number of hydrogen nuclei associated with the fluids in the pores within the sensitive volume. This amplitude is calibrated in porosity units (see Eq.1). Porosity was one of the earliest NMR measurements and is still an important one.

The determination of porosity is paramount because it determines the ultimate volume of a rock type that can contain hydrocarbons. The value and distribution of porosity, along with permeability and saturation, are the parameters that dictate reservoir development and production plans. Determination of porosity from a wireline log is only part of the problem, because the values determined in one well must be upscaled into the space between wells. To extrapolate correctly, the team must identify depositional environments and rock types and then have access to analog data sets. Only then can the correct statistical distributions be extrapolated across the reservoir.