The concept of portfolio diversification has been a widely accepted method for reducing uncertainty (risk) in financial markets since Harry Markowitz's work in the 1950s. In fact, one of the reasons financial institutions like oil and gas investments is, in part, due to the concept of portfolio optimization and the affect direct investment in these commodities has on their overall portfolio. In general, oil companies, however, have been less receptive to implementing these concepts.
First some basic portfolio optimization concepts. The basic idea is that while individual investments (properties, projects, etc) have their own unique set of parameters (ENPV-estimated net present value, risk, etc), when you combine these investments into a portfolio the interaction of these individual investments can alter the risk of the portfolio. This is best demonstrated by an example used in Ball & Savage Associates 1999 paper where you have $10MM to invest and two distinct projects to choose from. The first is a relatively "safe" investment and the second is relatively "risky," but the estimated NPV is the same for each.
ENPV(safe) = 60% * $50 + 40% * (-$10) = $26MM
ENPV(risky) = 40% * $80 + 60% * (-$10) = $26MM
The two projects are independent, that is to say the result of one doesn't affect the other. In this example the authors go on to suppose your job is dependent on not losing money. So, you can see with the "safe" project you only have a 40% chance of losing your job, but with the "risky" project you run a 60% chance of being fired. Since both projects have the same ENPV, most people would correctly choose to invest in the "safe" project.
However, in this example if you were allowed to invest half your money in each project the only way you could lose money is by both projects being unsuccessful (if one is successful it pays for the other being unsuccessful), and since they are independent, the chance of both being unsuccessful is 40% * 60% = 24%. So, by spreading your money between two projects instead of one "safe" project you have reduced your "risk" of unemployment from 40% down to 24%. This is the power of the "diversification effect" and is not intuitively obvious to most of us.
The effects of diversification can be even greater when the projects are not completely independent as stated above. If the projects are statistically dependent then the outcome of one will have an effect on the outcome of the other. If the outcome of one project increases the chance of a similar outcome in the other, then the projects are Positively Correlated. If, however, the outcome of one project reduces the chance of a similar outcome in the other, then they are Negatively Correlated.
In the above example, if the projects were positively correlated, then the 50/50 portfolio would have a greater than 24% change of getting you fired, but if they were negatively correlated you would have an even less than 24% chance of being sacked. The exact chance would depend on the degree of correlation. The idea here is risk can be minimized by spreading your investment across many projects and trying to avoid positive correlations while looking for negative correlations.
As I mentioned at the beginning, this is one reason institutional investors like direct investment in commodities such as oil and gas. Historically, direct investment in oil and gas has had a relatively strong negative correlation to more traditional investments (stocks and bonds). So by including some oil and gas investments in a traditional portfolio the "risk" of the entire portfolio can be reduced and moved closer the "efficient frontier" as advocated by Markowitz; of course there are other reasons to invest in oil and gas as Kathy Heshelow outlines on her web site.
These concepts are used by some of the larger oil companies and mostly in determining exploration programs, but my experience is that they are not being used by most of the smaller companies and rarely when looking at A&D programs. While there are computer programs that can simulate this portfolio effect, most of the smaller companies I am familiar with shy away from this methodology and prefer more intuitive investment strategies; specifically new start-ups who prefer to get their capital invested quickly and would rather take 100% of fewer projects rather than "spread the risk" and delay getting their capital in play.
The general concepts of portfolio optimization can be applied without having to perform the rigorous calculations or build complex computer models simply by practicing diversification and spreading the risk around (several smaller deals instead of fewer big ones) and looking for negatively correlated projects.