Layer | Fill | Outline |
---|
Map layers
Theme | Visible | Selectable | Appearance | Zoom Range (now: 0) |
---|
Fill | Stroke |
---|---|
Collaborating Authors
Results
Abstract We present the technical basis for bridging the wide structure data-gap at the heart of the oil and gas production business: the scale of geological detail in the range between a few tens of centimetres to a few meters. This scale range is at least an order of magnitude smaller than is resolvable with current means. Many reservoir properties such as permeabilities are largely determined by the microscale behaviour of pore geometries and pore throats in the range down to millimetres or less. The underlying unifying concept is that broadband vector seismic data contain a wealth of information regarding rock fabric and fluid content. Careful seismic field experiments, observation and data analysis can bridge the gap in the spatial knowledge of the reservoir between the very detailed, but laterally very limited information provided by borehole logging data and the spatially extensive but diffuse structural information provided by 3D seismic data. Measurements obtained in boreholes and aimed specifically at capturing certain elastic formation parameters are related through the geophysical model to reservoir parameters of direct engineering and economic interest in a series of "snapshots" of in situ distributions of fluids and rock masses, taken at opportune moments in the life of the reservoir and representing a substantial amount of reservoir volume in centimetre to metre detail. Introduction A fundamental feature of rock is the multiple length scales at which physical processes take place. A prime example is rock permeability: petrophysical structures from submillimetre to kilometre sizes control and delineate the permeability of a rock volume. Hydrocarbon production within a field can vary substantially from well to well. Reservoir heterogeneity, such as shales in sands, sand bodies in shales, changes in facies and spatial variability of porosity, permeability and fluid satuiation, is the main cause for the variations in productivity and the relatively low rate of recovery of total reserves. These heterogeneities prevent easy understanding of where hydrocarbons are collected and how they move or are driven to the producing wells. If all the reservoirs within a given field can be located, and if the heterogeneities within the reservoirs can be defined with greater precision than at present, substantially more oil will be produced from existing fields even without improved oil recovery techniques. Efficient reservoir appraisal and management requires reliable answers to following questions:Where are the hydrocarbons located in the reservoir and how are they distributed between reservoirs? What is their total volume in place and what percentage of it can we expect to recover economically? Where are production wells to be located, what can they be expected to produce individually and how many are required to achieve economically attractive and technically sustainable production? Will any or all of them be required to be extended-reach or horizontal wells?
- Geology > Geological Subdiscipline > Geomechanics (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.45)
- Geophysics > Seismic Surveying > Surface Seismic Acquisition (1.00)
- Geophysics > Seismic Surveying > Seismic Processing (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling > Velocity Modeling (0.46)
HESPER: An Expert System for Petrophysical Formation Evaluation
Peveraro, R.C.A. (Britoil plc) | Lee, J.A. (Britoil plc)
Abstract A prototype expert system for formation evaluation is introduced and discussed, beginning with the rationale for its development and presenting briefly qualitative assessments and tests of its performance. The background and definition of petrophysical formation evaluation is clarified, and the specific geological frame of the Permian Southern Basin of the North Sea, in which the system operates, is presented, with indications of future developments. The different modules of the system are discussed in some detail, and the interaction between modelling, advice-giving, and the user interface is clearly shown to be a crucial factor. Of particular importance is the ability of the system of presenting the reasons for its choice of solution in a clear text and in a user-intelligible fashion. Tests and performance of the system are discussed from a qualitative viewpoint, rather than after rigorous benchmark tests. This is considered appropriate at this stage, since the system is by no means in its final configuration. The conclusion has been reached by Britoil that the system has demonstrated that the application of expert systems design and technology to petrophysical formation evaluation is both petrophysical formation evaluation is both feasible and desirable, and further development would therefore be beneficial. 2. DEFINITION OF THE PROBLEM The HESPER system (or Heuristic Expert System for the Petrophysical Evaluation of Reservoirs) attempts to emulate the manual process of Petrophysical Interpretation. Petrophysical Interpretation. The system takes wireline log data, along with drilling coring and other data, and allows the petrophysicist to build and manipulate a petrophysicist to build and manipulate a geological model of the formation. Using petrophysical equations, synthetic logs can be petrophysical equations, synthetic logs can be generated from this model and compared, both visually and by the program, with the real logs recorded in the borehole. When a reasonable match is obtained with all pertinent logs, he model can be taken to represent adequately the formation under evaluation. This statement can be shown in diagrammatic form as a flow diagram (Fig. 1). Note that we have separated the process into two distinct phases, a data capturing phase, and a data interpretation phase. As indicated in the diagram, HESPER concerns itself with the data interpretation phase. The reasons for this are both conceptual and practical. Data obtained at the wellsite (wireline logs, cores, cuttings, drilling logs, etc.) are in general supplied to the client by different service companies, at different times, using different systems. Often they are in a mutually incompatible format, and in general they all have to be reduced to a common, corrected version, eliminating the influences of the drilling environment, borehole, tool response, etc. In other words, the "raw data signals" have to be processed and deconvolved into "formation processed and deconvolved into "formation response signals." P. 361
- Europe > North Sea (0.34)
- North America > United States (0.29)
- Europe > United Kingdom > North Sea (0.25)
- (3 more...)
- Geology > Sedimentary Geology > Depositional Environment (0.93)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.49)
- Geology > Mineral > Silicate > Phyllosilicate (0.47)
- North America > United States > Texas > Permian Basin > Yeso Formation (0.99)
- North America > United States > Texas > Permian Basin > Yates Formation (0.99)
- North America > United States > Texas > Permian Basin > Wolfcamp Formation (0.99)
- (22 more...)
ABSTRACT/Introduction Geophysical well logs can be used to determine subsurface lithological units. Currently available methods generally provide only qualitative descriptions based on crossplots of two well logs. Comprehensive error analysis within this method is not possible, so some information can be misinterpreted. Other investigators have proposed specifying the well logs as a linear system responding to the proportion of each lithology component. Signal processing and information theory techniques can then be employed to quantitatively determine these components and their associated errors. The general form for this system is L = CV, where L is the geophysical log response vector, C is the response coefficient matrix, and V is she lithological component proportions vector. Solutions are obtained for all combinations using under-determined, determined, and over-determined systems. The error computation allows the initial model to be modified and the results further improved. This technique can be generalized to include the computation of bulk volume estimates viewing the well logs as a linear system responding to variation in all geophysical parameters. It should, therefore, be possible to estimate from the solution of the general system not only the proportions of the lithological elements but also the proportion of the proportions of the lithological elements but also the proportion of the fluids filling the pore space. Known non-linear responses can be eliminated by prior processing or by appropriate linearization models of log responses. This is particularly required for resistivity and acoustic measurements. MATRIX METHOD OF LITHOLOGY DETERMINATION A fundamental method of determining lithology for simple formations is by means of the neutron-density crossplot (Fig. 1). Common mineral values are plotted as points. Recorded neutron and density log values allow determination of simple lithology units by noting the closest mineral points. When difficulties arise in determination of lithology, an points. When difficulties arise in determination of lithology, an additional crossplot, most commonly a sonic-neutron or a sonic-density, can be used to resolve any ambiguities. By assuming clean formations with a lithology consisting of only matrix and formation water, the porosity can be determined from any single log response. Neutron: (Eq. 1) Density: (Eq. 2) Sonic: (Eq. 3) , , represent porosity based on individual log response. log' , log recorded log responses. , log responses assuming 100 matrix. , log responses assuming 100% formation water. Corresponding porosity lines have been plotted for matrix values of sandstone, limestone, and dolomite (Fig. 1). This method of determining lithology mathematically describes a set of linear equations 4. Each lithology volume is based on the location of the mineral points and the recorded log responses, which can be generalized to state that each recorded log response is a linear function of the lithology volume present. p. 29
- North America > United States (0.68)
- Europe > Norway > Norwegian Sea (0.24)
- Geology > Rock Type > Sedimentary Rock > Carbonate Rock (0.54)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Sandstone (0.35)
- Asia > Middle East > Kuwait > Jahra Governorate > Arabian Basin > Widyan Basin > North Kuwait Jurassic (NKJ) Fields > Marrat Formation > Upper Marrat Formation (0.98)
- Asia > Middle East > Kuwait > Jahra Governorate > Arabian Basin > Widyan Basin > North Kuwait Jurassic (NKJ) Fields > Marrat Formation > Sargelu Formation (0.98)