With each succeeding generation of technology, recoverable reserves increase in mature fields. However, there can be challenges because, despite the amount of information that is available, mature fields can be complex. The key is a robust reservoir model. Welcome to an interview with Sharma Dronamraju, AKD Professional Solutions, who discusses the best ways to build reservoir models and plan to revitalize a mature field.

What is your name and your background in geosciences?

My name is Sharma Dronamraju. I graduated with MS-Applied Geology from Indian Institute of Technology at Kharagpur. I worked for the oil industry for few years before going back to school to learn more Geophysics and Petroleum Engineering at Texas A&M University for MS-Geology. More recently, I did my MBA from Rice University. My early work was mostly in frontier exploration geology and well-operations where I gained expertise in estimating overpressures and mitigating drilling complications. I developed algorithms to monitor and estimate pore-and fracture pressure and stress gradients in subsurface. I worked with Fugro, in the deep-water geohazards market all over the world; with Halliburton in selling geophysical technology, real-time asset development projects, reservoir modeling, conducting full-field reviews and brownfield development for several large IOCs and NOCs; with Marathon Oil in the development of large offshore deep-water fields in West Africa, North Sea, Gulf of Mexico, and exploration for unconventional resources such as shale gas, oil sands, CBM in several basins of the world; and Petrobras, in production and development of deep-water fields. I have also worked as consultant in developing several mature oil and gas fields in Malaysia, India, North Sea, Colombia, Nigeria, Argentina, and onshore US.

What are some of your main interests?

My main interests are Structural Geology, Tectonics, Paleogeography, and Reservoir Modeling. I build robust static models that serve every decision that we make on an asset, as well as serve as an up-to-date data repository of the asset. A full-field reservoir model could effectively hold the cumulative result of total geological history; it must be consistent with regional geology, which means agreeing with possible updip and downdip extensions of the field; the local structure and stratigraphy must agree with regional markers and unconformities; hydrocarbon content, column heights, and entrapment must be consistent with charge system for the play.

What appeals to you about mature fields? Do you think that the rewards outweigh the risks? How and when?

I guess it is the challenge they pose. In exploration, field discoveries have been made with less than 25% Chance of Success. There is a thrill of serendipity. Ironically, a discovery is a celebration of ingenuity in retrospect. We make science until we drill the next dry hole! In contrast, mature fields have 0% risk on the prospect and have large quantity of data, "big data" that we refer to in the Information Technology world (Fig 1). We are living in conditions that demand lowering the cost of production and questioning the conventional wisdom. Our success depends very little on what we have learned, but more on what we can apply and prove. 70% world's oil is still locked up in the complex pore-spaces of rocks by simple physical processes such as capillarity and hydrodynamics, hidden behind the subtle features of stratigraphy, simply by inadequate technology or poor economics. Increasing recovery factor even by 1% means ~88Bbbl of oil, equivalent to 3 years of global production. We have produced about a trillion barrels in 20th century, which is less than half of the world's estimated recoverable reserves.

Certainly, the challenges are rewarding. I think there is a real satisfaction in pushing the boundaries of science. Shale revolution is one extreme example of that. It is true that we are hurt by our own success at this moment.

It was not a controlled experiment - we tipped the supply curve, and the fall-out has been brutal. World economies are more interlinked today than they were 30 years ago. In this low-price environment, we must be innovative to drive-down costs to make money with the "New Normal"! Overhauling mature fields is the key. At least, we can keep the gambling out of the equation for now. Often I see that mature fields do not get the geology help they deserve. A Geologist's time is engaged in meeting the everyday needs of production operations, and for the mature fields this realization comes after ~10 years, after a full-field review.

What are the "must have" technologies for mature fields reservoir characterization?

I could be biased here, but I will try to paint the big picture.

1. 

   Fig. 4. High-resolution field-scale sequence stratigraphy offers valuable guidance in predicting and isolating reservoirs, seals, and upside field potential.
   Subsurface imaging field-scale: Acquiring state-of-the-art 3D seismic data over the field and over the play trend, because chances are size of the field grows with 3D seismic. The science of seismic acquisition, processing technology, and imaging have grown many folds in the last 10 years. Some of the fields I worked in had no 3D seismic! Seeing is believing. Investment is worth every penny here (Fig 3).
2. Imaging at pore-scale: Digital imaging of pore-space in rocks is gaining popularity for a reason. High resolution petrophysics, better understanding of pore structure, distribution, rock fabric at micro-scale, etc. enable us to characterize facies and reservoirs, especially in complex carbonate reservoirs which are more sensitive to diagenesis. This information is vital for reservoir characterization and EOR.
3. Modeling technology. Due to the hardware limitations and several days of run-times, the models must be up-scaled to lower resolution. However, with advancements in hardware, simulators, and now Cloud computing, the reservoir models can have several million cells. Geologists can now build sophisticated models, preserving details from pore-scale to sub-seismic stratal architecture.

Besides these, there are several other areas that influence reservoir characterization in data acquisition and processing in real-time, which greatly enhance our ability to understand reservoirs, in real time, so that production from mature fields can be predicted and managed more precisely, just like a well-maintained car gives better mileage.

What are new techniques that you have tried and are successful in mature fields reservoir optimization?

Successful exploitation of mature fields requires understanding the subsurface geology. Every tool that is developed should have this same purpose. I would not say these are techniques or magic buttons, but certainly getting back to the basics of Geology should help. I investigate geology of any field "ground-up". I leverage all sources data, at all scales, to paint as realistic a picture as possible of paleogeography. I work through the tectonic history, record events responsible for current basin, and apply predictive sequence stratigraphy at the field-scale (Fig 4). Understanding basin dynamics and agents far bigger than field size often determine the field potential and behavior. Good examples are salt tectonics in the GoM and Europe, tectonics of South China Sea (Fig 5), aquifer systems in onshore heavy oil fields in Latin America, oil sands of Canada, and intertidal carbonates and clastics of West Texas Permian Basin, where major discoveries are made even today using modern technology and ideas.

Nothing engages a geologist more than correlating wells, sort of a Geologist's turf. I spend good amount of time reviewing field-wide correlations, and question every notion considering current information (Fig 6). I also start with production allocation data, where there is significant production. I build a comprehensive reservoir model, considering every aspect of subsurface information.

What are some of the new directions in the path ahead?

In managing mature fields, I see a major push in data gathering, automation, real-time data access and processing. Shared earth models and visualization technologies have been in place for many years. But much of data feed into models is still manual and lacks consistency across the industry. When 3D seismic was new in 80s, it took several years to have standards to come in place. A comprehensive reservoir model is central to managing a mature field, which is still considered an art, and probably it will be for some time. Managing mature fields require standardizing and discipline in many areas of geology and engineering that feed into building and maintaining a central reservoir model.

What do you expect will happen in a) a continued low price environment; b) when the prices go up?

It is difficult to predict how oil prices swing in future. But we already have a good sample of two years of low prices of oil. When cash-flows trickled, operators had to produce more to make the same money. Mature fields came to the rescue, due to the low-risk and low-cost of ownership. Many of these have been revisited with better technology in seismic and drilling with increased efficiencies, which further reduced costs. Operators pulled from deep-water investments. There have been few mergers and consolidation. Market space favored independents and land owners. This will continue.

When the prices go up logical thing is to expect investments in large onshore plays land acquisition, in deep-water, and probably more mergers. But mature field efficiencies will remain as cash flow generators. Sophisticated partnerships would replace some technology supplier and service models.

Can you recommend articles to read?

I wish I could recommend. Mature fields require specialists from many disciplines in Geoscience and Engineering. But I have been reading on Continental Rift basins, Carbonates, Permian Basin and comparing them to present-day analogs in the Middle East, and the Late Permian and Mesozoic history of North American continent. Carbonates probably hold more than 50% of world's reserves. In fact, I am revisiting teachings from graduate school, capillary pressures by Robert R. Berg, Wayne Ahr, and my mentors from my early career.