scholarly journals The PetroPhysical Property Database (P<sup>3</sup>) – a global compilation of lab-measured rock properties

2020 ◽  
Vol 12 (4) ◽  
pp. 2485-2515
Author(s):  
Kristian Bär ◽  
Thomas Reinsch ◽  
Judith Bott
Keyword(s):  
Numerical Models ◽  
Laboratory Data ◽  
Rock Properties ◽  
Petrophysical Properties ◽  
Geophysical Investigation ◽  
Geothermal Exploration ◽  
Accessible Information ◽  
In Situ Conditions ◽  
Investigation Methods ◽  
Geophysical Surveys

Abstract. Petrophysical properties are key to populating local and/or regional numerical models and to interpreting results from geophysical investigation methods. Searching for rock property values measured on samples from a specific rock unit at a specific location might become a very time-consuming challenge given that such data are spread across diverse compilations and that the number of publications on new measurements is continuously growing and data are of heterogeneous quality. Profiting from existing laboratory data to populate numerical models or interpret geophysical surveys at specific locations or for individual reservoir units is often hampered if information on the sample location, petrography, stratigraphy, measuring method and conditions is sparse or not documented. Within the framework of the EC-funded project IMAGE (Integrated Methods for Advanced Geothermal Exploration, EU grant agreement no. 608553), an open-access database of lab-measured petrophysical properties has been developed (Bär et al., 2017, 2019b: P3 – database, https://doi.org/10.5880/GFZ.4.8.2019.P3. The goal of this hierarchical database is to provide easily accessible information on physical rock properties relevant for geothermal exploration and reservoir characterisation in a single compilation. Collected data include classical petrophysical, thermophysical, and mechanical properties as well as electrical conductivity and magnetic susceptibility. Each measured value is complemented by relevant meta-information such as the corresponding sample location, petrographic description, chronostratigraphic age, if available, and original citation. The original stratigraphic and petrographic descriptions are transferred to standardised catalogues following a hierarchical structure ensuring inter-comparability for statistical analysis (Bär and Mielke, 2019: P3 – petrography, https://doi.org/10.5880/GFZ.4.8.2019.P3.p; Bär et al., 2018, 2019a: P3 – stratigraphy, https://doi.org/10.5880/GFZ.4.8.2019.P3.s). In addition, information on the experimental setup (methods) and the measurement conditions are listed for quality control. Thus, rock properties can directly be related to in situ conditions to derive specific parameters relevant for simulating subsurface processes or interpreting geophysical data. We describe the structure, content and status quo of the database and discuss its limitations and advantages for the end user.

scholarly journals P<sup>3</sup> – PetroPhysical Property Database – a global compilation of lab measured rock properties

2020 ◽  
Author(s):  
Kristian Bär ◽  
Thomas Reinsch ◽  
Judith Bott
Keyword(s):  
Numerical Models ◽  
Laboratory Data ◽  
Rock Properties ◽  
Petrophysical Properties ◽  
Geophysical Investigation ◽  
Geothermal Exploration ◽  
Accessible Information ◽  
In Situ Conditions ◽  
Investigation Methods ◽  
Geophysical Surveys

Abstract. Petrophysical properties are key to populate local and/or regional numerical models and to interpret results from geophysical investigation methods. Searching for rock property values measured on samples from a specific rock unit at a specific location might become a very time-consuming challenge given that such data are spread across diverse compilations and that the number of publications on new measurements is continuously growing and data are of heterogeneous quality. Profiting from existing laboratory data to populate numerical models or interpret geophysical surveys at specific locations or for individual reservoir units is often hampered if information on the sample location, petrography, stratigraphy, measuring method and conditions are sparse or not documented. Within the framework of the EC funded project IMAGE (Integrated Methods for Advanced Geothermal Exploration, EU grant agreement No. 608553), an open-access database of lab measured petrophysical properties has been developed (Bär et al., 20182019: P3 – Database, https://doi.org/10.5880/GFZ.4.8.2019.P3). The goal of this hierarchical database is to provide easily accessible information on physical rock properties relevant for geothermal exploration and reservoir characterization in a single compilation. Collected data include classical petrophysical, thermophysical and mechanical properties and, in addition, electrical conductivity and magnetic susceptibility. Each measured value is complemented by relevant meta-information such as the corresponding sample location, petrographic description, chronostratigraphic age, if available, and original citation. The original stratigraphic and petrographic descriptions are transferred to standardized catalogues following a hierarchical structure ensuring inter-comparability for statistical analysis (Bär et al., 2019: P3 – Petrography, https://doi.org/10.5880/GFZ.4.8.2019.P3.p, Bär et al., 20182019: 3 – Stratigraphy, https://doi.org/10.5880/GFZ.4.8.2019.P3.s. In addition, information on the experimental setup (methods) and the measurement conditions are listed for quality control. Thus, rock properties can directly be related to in-situ conditions to derive specific parameters relevant for simulating subsurface processes or interpreting geophysical data. We describe the structure, content and status quo of the database and discuss its limitations and advantages for the end-user.

scholarly journals Integrated petroelectrical models of devonian limestones and cambrian sandstones from Dobrotvirska area of Volyno-Podilia

2014 ◽  
pp. 25-30
Author(s):  
S. Vyzhva ◽  
D. Onyshchuk ◽  
N. Reva ◽  
V. Onyshchuk
Keyword(s):  
Water Saturation ◽  
Laboratory Data ◽  
Effective Porosity ◽  
P Wave ◽  
Rock Properties ◽  
Residual Water ◽  
Specific Resistivity ◽  
Filtration Method ◽  
Reservoir Rocks ◽  
In Situ Conditions

This paper deals with the technique and results of research into petroelectrical properties of complex terrigenous and carbonate reservoirs. Analyzed are electric data and their relation to capacity properties of Devonian limestones and Cambrian sandstones from Dobrotvirska area of Volyno-Podilia. The objective of the research was to build petroelectrical models of reservoir rocks based on the electrical parameters and their relation to capacity properties. Data on specific resistivity of reservoir rocks were used for specifying the range of its variation for different types and groups of rocks. These data were also essential for identifying the stratigraphic horizons, cross-sections and facies, as well as finding the relationship between specific resistivity and a range of factors such as mineral composition, pore structure, substance phase ratio, electric field intensity and frequency, and resistivity variations with epigenetic transformation and metamorphic changes in rocks. Laboratory data on electrical resistivity of rocks made it possible to interpret the results of employing electrometric well logging methods and electric exploration. Petrophysical laboratory data enabled us to determine the following properties: rock density (dry and saturated with synthetic brine), effective porosity (nitrogen and synthetic brine saturation methods), residual water saturation factor (by centrifugation), permeability (nitrogen stationary filtration method), interval time (P-wave velocity) and resistivity. There were obtained laboratory data on specific resistivity of rock samples (dry, partly and fully saturated with synthetic brine) in atmospheric and in simulated in-situ conditions. We estimated the petroelectrical parameters of Cambrian sandstones and Devonian limestones from Dobrotvirska area to find an empirical correlation between petroelectrical parameters, porosity and permeability of the studied rocks. The correlations are mainly approximated by power function and serve as the basis for geological interpretation of geophysical data. Electrometric methods have proved to be a powerful tool in both laboratory and field rock studies, being efficient enough to provide extensive information on rock properties.

Machine Learning for Multiple Petrophysical Properties Regression Based on Core Images and Well Logs in a Heterogenous Reservoir

2021 ◽  
Author(s):  
Tao Lin ◽  
Mokhles Mezghani ◽  
Chicheng Xu ◽  
Weichang Li
Keyword(s):  
Machine Learning ◽  
Model Building ◽  
Image Features ◽  
Well Logs ◽  
Model Complexity ◽  
Rock Properties ◽  
Core Analysis ◽  
Petrophysical Properties ◽  
Blind Test ◽  
Porosity And Permeability

Abstract Reservoir characterization requires accurate prediction of multiple petrophysical properties such as bulk density (or acoustic impedance), porosity, and permeability. However, it remains a big challenge in heterogeneous reservoirs due to significant diagenetic impacts including dissolution, dolomitization, cementation, and fracturing. Most well logs lack the resolution to obtain rock properties in detail in a heterogenous formation. Therefore, it is pertinent to integrate core images into the prediction workflow. This study presents a new approach to solve the problem of obtaining the high-resolution multiple petrophysical properties, by combining machine learning (ML) algorithms and computer vision (CV) techniques. The methodology can be used to automate the process of core data analysis with a minimum number of plugs, thus reducing human effort and cost and improving accuracy. The workflow consists of conditioning and extracting features from core images, correlating well logs and core analysis with those features to build ML models, and applying the models on new cores for petrophysical properties predictions. The core images are preprocessed and analyzed using color models and texture recognition, to extract image characteristics and core textures. The image features are then aggregated into a profile in depth, resampled and aligned with well logs and core analysis. The ML regression models, including classification and regression trees (CART) and deep neural network (DNN), are trained and validated from the filtered training samples of relevant features and target petrophysical properties. The models are then tested on a blind test dataset to evaluate the prediction performance, to predict target petrophysical properties of grain density, porosity and permeability. The profile of histograms of each target property are computed to analyze the data distribution. The feature vectors are extracted from CV analysis of core images and gamma ray logs. The importance of each feature is generated by CART model to individual target, which may be used to reduce model complexity of future model building. The model performances are evaluated and compared on each target. We achieved reasonably good correlation and accuracy on the models, for example, porosity R2=49.7% and RMSE=2.4 p.u., and logarithmic permeability R2=57.8% and RMSE=0.53. The field case demonstrates that inclusion of core image attributes can improve petrophysical regression in heterogenous reservoirs. It can be extended to a multi-well setting to generate vertical distribution of petrophysical properties which can be integrated into reservoir modeling and characterization. Machine leaning algorithms can help automate the workflow and be flexible to be adjusted to take various inputs for prediction.

Application of Computational Intelligence in Generating Synthetic Reservoir Rock Mechanical Parameters for Building Geo-Models.

2015 ◽  
Author(s):  
L. C. Akubue ◽  
A.. Dosunmu ◽  
F. T. Beka
Keyword(s):  
Neural Network ◽  
Statistical Analysis ◽  
Numerical Models ◽  
Petroleum Industry ◽  
Oil Field ◽  
Wellbore Stability ◽  
Reservoir Rock ◽  
Rock Properties ◽  
Earth Model ◽  
Sonic Log

Abstract Oil field Operations such as wellbore stability Management and variety of other activities in the upstream petroleum industry require geo-mechanical models for their analysis. Sometimes, the required subsurface measurements used to estimate rock parameters for building such models are unavailable. On this premise, past studies have offered variety of methods and investigative techniques such as empirical correlations, statistical analysis and numerical models to generate these data from available information. However, the complexity of the relationships that exists between the natural occurring variables make the aforementioned techniques limited. This work involves the application of Artificial Neural Networks (ANNs) to generating rock properties. A three-layer back-propagation neural network model was applied predicting pseudo-sonic data using conventional wireline log data as input. Four well data from a Niger-Delta field were used in this study, one for training, one for validating and the two others for generating and testing results. The network was trained with different sets of initial random weights and biases using various learning algorithms. Root mean square error (RMSE) and correlation coefficient (CC) were used as key performance indicators. This Neural-Network-Generated-Sonic-log was compared with those generated with existing correlations and statistical analysis. The results showed that the most influential input vectors with various configurations for predicting sonic log were Depth-Resistivity-Gamma ray-Density (with correlating coefficient between 0.7 and 0.9). The generated sonic was subsequently used to compute for other elastic properties needed to build mechanical earth model for evaluating the strength properties of drilled formations, hence optimise drilling performance. The models are useful in Minimizing well cost, as well as reducing Non Productive Time (NPT) caused by wellbore instability. This technique is particularly useful for mature fields, especially in situations where obtaining this well logs are usually not practicable.

scholarly journals Estimation of Irregular Wave Runup on Intermediate and Reflective Beaches Using a Phase-Resolving Numerical Model

2020 ◽  
Vol 8 (12) ◽  
pp. 993
Author(s):  
Jonas Pinault ◽  
Denis Morichon ◽  
Volker Roeber
Keyword(s):  
Time Series ◽  
Best Practices ◽  
Numerical Models ◽  
Laboratory Data ◽  
Irregular Waves ◽  
Wave Transformation ◽  
Model Parameters ◽  
Wave Runup ◽  
Data Set ◽  
Promising Alternative

Accurate wave runup estimations are of great interest for coastal risk assessment and engineering design. Phase-resolving depth-integrated numerical models offer a promising alternative to commonly used empirical formulae at relatively low computational cost. Several operational models are currently freely available and have been extensively used in recent years for the computation of nearshore wave transformations and runup. However, recommendations for best practices on how to correctly utilize these models in computations of runup processes are still sparse. In this work, the Boussinesq-type model BOSZ is applied to calculate runup from irregular waves on intermediate and reflective beaches. The results are compared to an extensive laboratory data set of LiDAR measurements from wave transformation and shoreline elevation oscillations. The physical processes within the surf and swash zones such as the transfer from gravity to infragravity energy and dissipation are accurately accounted for. In addition, time series of the shoreline oscillations are well captured by the model. Comparisons of statistical values such as R2% show relative errors of less than 6%. The sensitivity of the results to various model parameters is investigated to allow for recommendations of best practices for modeling runup with phase-resolving depth-integrated models. While the breaking index is not found to be a key parameter for the examined cases, the grid size and the threshold depth, at which the runup is computed, are found to have significant influence on the results. The use of a time series, which includes both amplitude and phase information, is required for an accurate modeling of swash processes, as shown by computations with different sets of random waves, displaying a high variability and decreasing the agreement between the experiment and the model results substantially. The infragravity swash SIG is found to be sensitive to the initial phase distribution, likely because it is related to the short wave envelope.

Fluid-Hammer Effects on Coiled-Tubing Friction in Extended-Reach Wells

SPE Journal ◽  
2016 ◽  
Vol 22 (01) ◽  
pp. 365-373 ◽  
Author(s):  
Silviu Livescu ◽  
Steven Craig ◽  
Bill Aitken
Keyword(s):  
Friction Force ◽  
Numerical Models ◽  
Laboratory Data ◽  
Friction Reduction ◽  
Friction Modeling ◽  
Radial Vibrations ◽  
Friction Forces ◽  
Planning Stage ◽  
Force Matching ◽  
Coiled Tubing

Summary The lateral reach and residual bottomhole-assembly (BHA) loads in extended-reach wells strongly depend on the coiled-tubing (CT) mechanical friction. Detailed CT-friction modeling becomes crucial in the prejob planning stage to ensure successful job predictability. However, current numerical simulators consider constant coefficients of friction (CoFs) that are determined from similar operations without taking into account the effects of the operational and downhole parameters on the CoF for a specific operation. This study outlines the modeling of CT-friction force, CoF, and axial BHA loads depending on the operational and downhole parameters when a fluid-hammer tool is used. Recent theoretical, laboratory, and field data have established how CoF depends on the downhole parameters (Livescu and Wang 2014; Livescu and Watkins 2014; Livescu et al. 2014a, b; Livescu and Craig 2015). Previously, these effects were not considered in the CT numerical models, leading to significant CoF differences among available commercial simulators. For instance, the default CoFs in the current prejob simulations for cased holes, when no lubricant or friction-reducing tools such as fluid-hammer tools and tractors are used, vary between 0.24 and 0.30 or even higher. This makes it extremely difficult to consistently evaluate and compare the friction-reduction effects of lubricants, fluid-hammer tools, and tractors in extended-reach wells, especially when the field operator may be consulting with several service companies that use different commercial force-modeling software. This study presents the CT-force matching and fundamental physics on the basis of modeled fluid forces, including radial forces, drag forces, and, most importantly, pressure forces on the CT-friction forces caused by fluid-hammer tools. Extending the method of characteristics, regularly used for studying pressure pulses in straight pipes, the perturbations method also accounts for the helical shape of the CT. The new CT fluid-hammer model is validated against laboratory data. This rigorous method for calculating the axial BHA load and reduced CT-friction force caused by radial vibrations can be easily implemented in currently available tubing-force analysis (TFA) software for CT operations. This novel approach, which uses detailed CT mechanical-friction modeling to take into account parameters such as temperature, internal pressure, pumping rate, and others, improves predictions for CT reach in lateral wells. These findings broaden the current industry understanding of the CT mechanical friction modeling in extended-reach wells, and show benefits for the industry when considering variable friction modeling in commercial CT simulators.

Advances in understanding localised variations in deformation experiments using numerical models

2020 ◽  
Author(s):  
Sebastian Cionoiu ◽  
Lucie Tajčmanová ◽  
Lyudmila Khakimova
Keyword(s):  
Grain Size ◽  
Phase Transitions ◽  
Subduction Zones ◽  
Numerical Models ◽  
3D Models ◽  
Rock Properties ◽  
Stress And Strain ◽  
Transition Distribution ◽  
Pressure Stress ◽  
2D And 3D

&lt;p&gt;Phase transitions affect the physical properties of rocks (e.g. rheology) and control geodynamic processes at different spatial and time scales. However, the influence of deformation on phase transitions and their coupling is not well understood.&amp;#160;&lt;br&gt;Previous experiments, with both assembly-induced and additionally placed mechanical heterogeneities, have shown patterns in the phase transition distribution. Numerical modelling (2D, viscous finite difference models) have been used to correlate the experimental observations with the mechanic stress state. The locally increased mean stress in the models shows the best correlation with the formation of high-pressure polymorphs in experiments (Cionoiu et al. 2019).&lt;br&gt;Besides the distribution of polymorphs, grain-size and deformation patterns also vary across the samples due to stress, strain and pressure variations. To better understand the mechanisms contributing to these variations, we used advanced numerical models (3D, viscoelastic) to calculate the local distribution of first order parameters as pressure, stress and strain. The modelled stress and strain patterns are compared to the experimentally produced phase transformation distribution and previous (2D) modelling results. The 2D and 3D models differ partially regarding the quantification of local stresses &amp;#8211; an effect that mainly depends on sample geometry (coaxial vs. general-shear). However, the qualitative fit between experiments, 2D and 3D models persists (i.e. the localisation of increased stresses or strain).&lt;br&gt;This contribution shows how numerical models, that closely represent the sample, can further improve the understanding of processes occurring in deformation experiments. Our new results emphasize that mechanically-induced stress-variations influence the grain-size and mineralogy of rocks which feeds back on their rheology.&lt;/p&gt;&lt;p&gt;References: &lt;br&gt;Cionoiu, S., Moulas, E. &amp; Taj&amp;#269;manov&amp;#225;, L. Impact of interseismic deformation on phase transformations and rock properties in subduction zones. Sci Rep 9, 19561 (2019)&lt;/p&gt;

Bringing slow slip processes into focus

2020 ◽  
Author(s):  
Rebecca Bell
Keyword(s):  
High Resolution ◽  
Subduction Zones ◽  
Seismic Velocity ◽  
Numerical Models ◽  
Fluid Pressure ◽  
Geophysical Methods ◽  
Rock Properties ◽  
Slow Slip ◽  
Velocity Models ◽  
The North

&lt;p&gt;The discovery of slow slip events (SSEs) at subduction margins in the last two decades has changed our understanding of how stress is released at subduction zones. Fault slip is now viewed as a continuum of different slip modes between regular earthquakes and aseismic creep, and an appreciation of seismic hazard can only be realised by understanding the full spectrum of slip. SSEs may have the potential to trigger destructive earthquakes and tsunami on faults nearby, but whether this is possible and why SSEs occur at all are two of the most important questions in earthquake seismology today. Laboratory and numerical models suggest that slow slip can be spontaneously generated under conditions of very low effective stresses, facilitated by high pore fluid pressure, but it has also been suggested that variations in frictional behaviour, potentially caused by very heterogeneous fault zone lithology, may be required to promote slow slip.&lt;/p&gt;&lt;p&gt;Testing these hypotheses is difficult as it requires resolving rock properties at a high resolution many km below the seabed sometimes in km&amp;#8217;s of water, where drilling is technically challenging and expensive. Traditional geophysical methods like travel-time tomography cannot provide fine-scale enough velocity models to probe the rock properties in fault zones specifically. In the last decade, however, computational power has improved to the point where 3D full-waveform inversion (FWI) methods make it possible to use the full wavefield rather than just travel times to produce seismic velocity models with a resolution an order of magnitude better than conventional models. Although the hydrocarbon industry have demonstrated many successful examples of 3D FWI the method requires extremely high density arrays of instruments, very different to the 2D transect data collection style which is still commonly employed at subduction zones.&lt;/p&gt;&lt;p&gt;&amp;#160;The north Hikurangi subduction zone, New Zealand is special, as it hosts the world&amp;#8217;s most well characterised shallow SSEs (&lt;2 km to 15 km below the seabed).&amp;#160; This makes it an ideal location to collect 3D data optimally for FWI to resolve rock properties in the slow slip zone. In 2017-2018 an unprecedentedly large 3D experiment including 3D multi-channel seismic reflection, 99 ocean bottom seismometers and 194 onshore seismometers was conducted along the north Hikurangi margin in an 100 km x 15 km area, with an average 2 km instrument spacing. In addition, IODP Expeditions 372 and 375 collected logging-while drilling and core data, and deployed two bore-hole observatories to target slow slip in the same area. In this presentation I will introduce you to this world class 3D dataset and preliminary results, which will enable high resolution 3D models of physical properties to be made to bring slow slip processes into focus. &amp;#160;&lt;/p&gt;

Hydrogeological controls on groundwater recharge in a weathered crystalline aquifer: A case study from the Makutapora groundwater basin, Tanzania

2020 ◽  
Author(s):  
Emanuel Zarate ◽  
Alan MacDonald ◽  
Russell Swift ◽  
Jonathan Chambers ◽  
Japhet Kashaigili ◽  
...  
Keyword(s):  
Groundwater Recharge ◽  
Crucial Role ◽  
Numerical Models ◽  
Groundwater Resources ◽  
Crystalline Rock ◽  
Aquifer Recharge ◽  
Crystalline Aquifer ◽  
Geophysical Surveys ◽  
Groundwater Basin ◽  
Semi Arid

&lt;p&gt;Drylands (semi-arid/arid regions) represent &gt;35% of the Earth&amp;#8217;s surface, support a population of around 2 billion people, and are forecast to be increasingly water stressed in coming decades. Groundwater is the most reliable source of water in drylands, and it is likely that the structure and hydraulic properties of superficial geology play a crucial role in controlling groundwater recharge in these regions.&amp;#160; However, the spatio-temporal hydrogeological controls on the rates of groundwater recharge, and their sensitivity to environmental change are poorly resolved.&lt;/p&gt;&lt;p&gt;In the Makutapora groundwater basin (Tanzania), an analogue for semi-arid tropical areas underlain by weathered and fractured crystalline rock aquifers, we conducted a series of geophysical surveys using Electrical Resistivity Tomography (ERT) and frequency domain electromagnetic methods (FDEM). Using these data, in conjunction with borehole logs, we identify and delineate five major lithological units in the basin: 1) Superficial deposits of coarse sand (&gt;200 &amp;#937; m) 2) Highly conductive smectitic clays (1-10 &amp;#937; m) 3) Decomposed pedolitic soils (30-100 &amp;#937; m) 4) Weathered saprolite (100-700 &amp;#937; m) and 5) Fractured granitic basement (&gt;700 &amp;#937; m). We also identify 10-50m wide zones of normal faulting extending across the basin and cutting through these units, interpreted with the aid of analysis of a digital elevation model alongside the geophysics data.&lt;/p&gt;&lt;p&gt;These results are combined with existing long-term hydrological and hydrogeological records to build conceptual models of the processes governing recharge. We hypothesise that: 1) Zones of active faulting provide permeable pathways enabling greater recharge to occur; 2) Superficial sand deposits may act as collectors and stores that slowly feed recharge into these fault zones; 3) Windows within layers of smectitic clay underlying ephemeral streams may provide pathways for focused recharge via transmission losses; and 4) Overbank flooding during high-intensity precipitation events that inundate a greater area of the basin increases the probability of activating such permeable pathways.&lt;/p&gt;&lt;p&gt;Our results suggest that configurations of superficial geology may play a crucial role in controlling patterns, rates and timing of groundwater recharge in dryland settings. They also provide a physical basis to improve numerical models of groundwater recharge in drylands, and a conceptual framework to evaluate strategies (e.g. Managed Aquifer Recharge) to artificially enhance the availability of groundwater resources in these regions.&lt;/p&gt;

GEOPHYSICAL ACTIVITY IN 1975

Geophysics ◽  
1976 ◽  
Vol 41 (4) ◽  
pp. 780-794 ◽  
Author(s):  
H. R. Espey
Keyword(s):  
Geophysical Methods ◽  
Groundwater Exploration ◽  
Computer Processing ◽  
Petroleum Exploration ◽  
Government Agencies ◽  
Survey Questionnaire ◽  
Geothermal Exploration ◽  
Unit Costs ◽  
Geophysical Surveys ◽  
Geophysical Techniques

This report provides statistics on worldwide use of geophysical methods in 1975. Data were obtained primarily through a survey questionnaire which was mailed out to more than 1500 companies, government agencies, and universities that use geophysical techniques for petroleum exploration, oceanography, engineering, mining, geothermal exploration, and groundwater exploration. Response to the survey was excellent and provided detailed information on more than 2100 geophysical surveys. Data on unit costs, methods used, and line‐miles covered are believed to be more accurate this year as a result of better cooperation from industry in filling out the questionnaires. Computer processing was utilized in tabulating the statistics to provide increased accuracy and detail. Data not supplied on the questionnaire for costs or line mileage were estimated on the basis of worldwide averages to produce a more comprehensive report.

Sign in / Sign up

Export Citation Format

Share Document