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WITH an annual turnover of some $100 million, including sales to the processing and general manufacturing markets, the international Transducer Division of Schlumberger Industries embraces five long‐established suppliers to the aircraft manufacturing and aerospace industries. The Division addresses itself to both the civil and military aerospace sectors from three strategic manufacturing locations—in the USA, UK and France. In the USA, there are two design, development and manufacturing operations at respectively Oxnard, California, and Newark in New Jersey. A similar total capability exists in the UK at Farnborough, Hampshire, and at Enfield in Middlesex where incidentally the Division also has its headquarters. The equally endowed French connection is situated at Velizy, on the outskirts of Paris.

The Schlumberger group has launched an international attack on the high‐tech sensor market, as Stephen McClelland explains.

FOLLOWING the successful launch of Schlumberger Instruments multi‐band‐width SI1215 Vibration Control System, the first in a series of control systems options, the 12155 — Classical Shock Option is now available. Offering instant switching between random and shock test routines, the SI12155 offers a cost effective means of system testing for commercial or military applications combining operational control simplicity and safety with a host of advanced upgrade features.

The corrosivity and competence of soils within Uburu and Okposi areas of the Southern Benue Trough, Nigeria, were evaluated using the electrical resistivity method. This paper aims to provide information that will aid pre-design of subsurface iron/steel pipe networks for distribution of pipe-borne water and construction of subsurface structures for agricultural and environmental purposes.

In total, 22 vertical electrical soundings (VES) in the Schlumberger configuration were acquired with Allied Ohmega™ Terrameter with a maximum half current (AB/2) electrode spacing of 200 m. Layer parameters were determined using partial curve matching techniques, using the Schlumberger master curves, while processing and modelling were done with the IPI2win™ software. The VES results were interpreted qualitatively and quantitatively to obtain various curve types and layer parameters, respectively, which were used to categorize the area into different competence and corrosivity zones. The first layer isoresistivity and competence maps were used to delineate four zones (A,B,C and D) with varying apparent resistivities and competences.

Incompetent soils with resistivity values ranging from 24.3-88.7 Om are found in Zone A. The soils in Zone A are mainly expansive clays which swell on absorption of water. Zone B contains moderately competent soils with resistivity values ranging from 273-308.6 Om, while Zones C and D are underlain by sandstones and contain competent to highly competent soils with resistivity values ranging from 511-750 Om and 835-1,525 Om, respectively. Zone E contains highly corrosive (24.3 Om) to mildly corrosive (102 Om) soils; Zone F contains soils that are essentially non-corrosive with resistivity values ranging from 271-1,525 Om, while the corrosivity of soils within Zone G varies from corrosive to mildly corrosive, with resistivity values ranging from 44.3-114 Om.

Some of the areas are not accessible because of community restrictions.

These findings are essentially very significant and should be taken into consideration when materials that are susceptible to corrosion are being considered for engineering, agricultural and environmental purposes in the area.

The findings will aid water resource planners and developers on how to protect metal pipes from corrosion, when used for water reticulation and agricultural purposes.

This paper fulfils an identified need to study the corrosivity of soils in the study area with a view to providing adequate protection to metal objects when being considered for water reticulation for domestic and agricultural purposes in the area.

Artificial neural network (ANN) is considered a good solution for building non-linear relationship between input and output parameters, which is suitable for solving production back allocation, which is the most important step for production planning of petroleum mine. The purpose of this paper is to suggest a solution for solving production back allocation problem at Samarang petrol mine based on ANN approach.

In this study, well operational parameters’ surveillance was conducted and ANN was used to build relationships between operation parameters and production rates. Experimental method is used for testing and evaluating the possibility of using ANN for supporting production planning at Samarang mine.

Consequently, the proposed ANN solution can increase the accuracy of predicted values and could be used for supporting production planning at Samarang mine. Because ANN uses well test data for training and predicting (without adding new devices), it could be a feasible and cheap solution.

There is a need for applying other methods, such as: support machine vector, non-linear autoregressive models, etc. for better evaluation of ANN solution.

The ANN models helped operation engineers to understand well production performance and make decision to improve production plan in timely manner. This solution could be generalized for the whole mine or to similar petroleum mines in practice.

This paper aims to propose a solution based on ANN for solving production back allocation problem of petroleum industry. The solution is tested at Samarang mine.

Moog have been selected to supply three models of their single stage electrohydraulic servovalve for the main fuel control system of the latest European military engine.