1. Field of the Invention
The invention relates to risk analysis in oil and gas prospecting. More particularly, it relates to the use of seismic attributes and supporting data quality to reduce the uncertainty of hydrocarbon presence and the uncertainty of accumulation size.
2. Description of the Prior Art
Oil and Gas exploration is typically a high-risk enterprise. Several geologic factors are needed to insure a petroleum accumulation. Prior to drilling, there are usually incomplete information and a variable quality of information regarding the necessary geologic factors. One important tool for pre-drill risk mitigation is seismic data.
For many years seismic exploration for oil and gas has involved the use of seismic energy sources and seismic receivers. The seismic receivers, the land based versions commonly called geophones and aquatic based versions called hydrophones, sense acoustic waves and produce electric signals indicative of the sensed waves.
In typical exploration practice, a source energy is generated by a seismic energy source, and when sensed, are transformed into electrical signals. The source wave travels into the surface of the earth and is reflected or refracted by subsurface geologic features. These reflections are detected by the phones and are converted to electric signals. These electric signals represent acoustic waves reflected from the interface between subsurface layers in the earth and form a continuous amplitude signal in time. The amplitude recording in time of the phone output at a single location is commonly called a seismic trace.
It is common practice for an arrangement of sources and receivers to be repeated in a predictable pattern, which then allows many seismic traces to be recorded. A collection of seismic traces, gathered in a repeatable way, forms a complete seismic survey. The source and receiver pattern within a seismic survey is generally repeated along a line, called two-dimensional data (2-D) or in some rectangular fashion covering an area, called three-dimensional data (3-D).
Modern seismic recording equipment transforms the analog signals produced by the phones to digital representations of the signal. These seismic traces are stored on a medium, such as magnetic tape, as digital samples. The digitized traces containing the reflection amplitudes from the earth can then be rearranged and processed by computer software to form a representative image of the earth""s subsurface layers.
One such technique in seismic processing is to form CMP (Common Mid-Point) gathers of seismic traces. The CMP technique groups together seismic traces with the same mid-point between the source and receiver. The traces within the CMP gather are further sorted by increasing distance between source and receiver. This distance between source and receiver is usually referred to as source-receiver offset.
FIG. 1 is a ray diagram detailing the CMP technique. For the case of a flat earth approximation, the CMP gather represents reflection signal from a common point on the interface between subsurface layers. FIG. 1 illustrates the seismic energy reflected from a subsurface interface for source-receiver offset pairs within a CMP gather. Note that in FIG. 1 all of the reflected energy corresponds to the same subsurface point but for differing source-receiver offsets.
FIG. 2 is an exemplary trace showing the gathering of a single subsurface point in the context of a CMP gather. This figure illustrates a single subsurface point within a CMP gather represented by a series of amplitude traces in time with increasing offsets between the source and receiver.
FIG. 3 is an exemplary embodiment of an equivalent time image of the subsurface reflection point or interface produced by ordering the traces in a line or over an area. To enhance signal from a single subsurface point, the reflection amplitudes within a CMP gather are flattened and then summed together (stacked) to eliminate noise or energy that does not correspond to the primary reflection. This process reduces each CMP gather to a single stacked trace. The amplitudes on the stacked trace represent different reflecting interfaces. Those skilled in the art can interpret this CMP stacked amplitude data as equivalent cross-sections of subsurface layers.
The primary use of CMP seismic data is to mitigate the pre-drill uncertainty in finding hydrocarbons. The following discussion, as summarized by FIGS. 4 through 8, outlines the basic elements of hydrocarbon risk analysis.
FIG. 4 is a geologic diagram of conditions for hydrocarbon accumulation. As depicted in FIG. 4, several unlikely geologic conditions should be satisfied for a hydrocarbon accumulation to exist. These geologic elements are (1) trap, (2) reservoir, (3) source, (4) timing, and (5) seal. The most common use for CMP data is to contour subsurface layers and identify the likely area for a trap.
The quality and quantity of the CMP data introduces uncertainty in this estimate. Similar uncertainty exists for each of the geologic elements. This uncertainty is quantified by assigning a probability factor between zero to one (0.0-1.0) to each geologic factor.
FIG. 5 is a probability diagram showing the determination of chance of petroleum accumulation. The product of these probability factors is usually designated Pg and indicates the chance that a petroleum accumulation exists. After all geologic elements have been investigated using the available data, the possible accumulation is referred to as a prospect.
FIG. 6 is a probability distribution curve for accumulation size. Associated with the chance that an accumulation exists, is the probability distribution for accumulation size. The size distribution depends on specifics within the geologic area, however the shape of the distribution remains the same. To those skilled in the art, this shape is referred to as lognormal. The range of values in the lognormal distribution for size can be very large or very small.
FIG. 7 is a probability distribution curve detailing the differences of the curves of FIG. 6. A small range in size distribution means that there is more certainty in the outcome, as illustrated in FIG. 7. The product of the probability distribution for size with the chance that an accumulation exists, Pg, determines the probability of finding a particular size of accumulation.
FIG. 8 is a distribution curve for a distribution estimate. This type of prospect risk analysis greatly aids a successful economic outcome of hydrocarbon exploration.
The use and interpretation of CMP data and its risk mitigation value continues to grow beyond simple mapping for trap. Seismic processing techniques are used to extract information from CMP amplitudes that more directly indicate the presence of hydrocarbons. These extracted attributes of CMP data are often called Direct Hydrocarbon Indicators or DHI""s. One example of a DHI attribute is the amplitude variation with offset (AVO) within a CMP gather.
FIG. 9 is an exemplary AVO graph. Under specific conditions, these offset amplitude variations are indicative of a gas reservoir. As is the case with the geologic factors for hydrocarbon accumulation, there is ambiguity in the seismic attributes for DHI""s.
Many typical analysis functions cannot empirically assess the risk and/or probability analysis in a cohesive integrated manner. As such, many intermediate steps have to be taken to achieve a subjective analysis of risk and/or probability factors, such as those discussed above, in the search for hydrocarbon bearing areas. Many other problems and disadvantages of the prior art will become apparent to one skilled in the art after comparing such prior art with the present invention as described herein.
Aspects of the invention are found in a risk analysis method, and a system for implementing such a method. In this invention, the seismic attributes are correlated versus data quality to give a relative indication of the possible success or economic viability of a particular prospect.
In one exemplary embodiment, a cross plot or matrix is formed of seismic attributes versus data quality. Seismic attributes indicative of hydrocarbons are assigned to the horizontal axis and measures of data quality are assigned to the vertical axis.
Positive seismic attributes of hydrocarbon cause a rightward shift along the horizontal axis. Negative seismic attributes of hydrocarbons cause a leftward shift along the horizontal axis.
Similarly, positive indicators of data quality cause an upward shift along the vertical axis and negative indicators of data quality cause a downward shift along the vertical axis. As confidence in data quality increase (upward shift) and positive seismic indicators of hydrocarbons increase (rightward shift), the confidence in finding hydrocarbons increases and the uncertainty in accumulation size decreases.
The upper right-hand corner of the DHI matrix represents the highest confidence in hydrocarbon presence and accumulation size. The upper left-hand corner of the DHI matrix represents high confidence that no hydrocarbons exist. The lower right-hand or left-hand comer indicates that there is no confidence, very high risk, in the presence of hydrocarbons, because data quality is sparse or of very poor quality.
Aspects of the present invention include the assignment of weights to the seismic attributes and to the data quality measures. These attributes and measures scale the response for a particular geologic province. If the geologic province is new or under-explored, it is possible to use the weights and scoring from an analogous area until drilling results in sufficient experience for matrix calibration are available.
As such, a system and method for objectively determining the risk assessment of a hydrocarbon prospect based on data quality and structural characteristics is envisioned. Other objects, advantages and novel features of the present invention will be apparent to those skilled in the art from the following detailed description of the invention, the appended claims, and in conjunction with the accompanying drawings.