August 22, 2012
Advanced Search
Home / Issue Archive / 2009 / October #10 / Developing Proved Commercial Hydrocarbon Reserves Technology for Offshore Fields

№ 10 (October 2009)

Developing Proved Commercial Hydrocarbon Reserves Technology for Offshore Fields

VNIIGAZ is Gazprom’s leading scientific research facility in the field of development and engineering of the gas industry technologies, including prospecting and development of gas fields; development of the offshore oil and gas resources; gas conversion and field conditioning; regulatory backup of components production, engineering and operation of the gas transport and underground storage system; mathematical modeling and information technologies.

By R. O. Samsonov, Yu. P. Ampilov, D. A. Mirzoyev

Share it!
   In 2008, a group of the VNIIGAZ scientists received the RF Government Award in the field of science and engineering for their work entitled “Developing Proved Commercial Hydrocarbon Reserves Technology for Offshore Fields by Example of Shtokman Gas Condensate Field.”

   With the bulk of Gazprom’s main gas fields going into decline, the problem of reserves replenishment for the gas industry became especially acute in the past few years. Over time, the situation with deficiency of active reserves has only worsened, and more customized solutions are required to resume the normal course of things. VNIIGAZ, the premier research facility of Gazprom, has developed its method of reserves treatment for remote regions that meets the challenges of time.

   The purpose of research was to develop a technology applicable for preparation of commercial reserves involving the minimum scope of expensive explorative drilling in harsh environment of the Arctic shelf seas. Meanwhile, some special recommended engineering practices should provide information on the fields, which would be sufficient and appropriate for the volume of commercial reserves.

    The research work yielded some results characterized by specific elements of scientific novelty, namely:
Criteria developed for typification of prospective features and deposits of hydrocarbons versus the extent of seismic and geological environment complexity.

   Methods and algorithms developed for appraisal of reservoir parameters and volumetrics within the crosshole space as well as the principles of their application in geologic model.

   A flow chart prepared of commercial reserves preparation depending on the complexity of seismo-geological conditions of prospected objects.
The expert review issued by the State Reserves Commission (SRC) recognized the substantiation of application of the produced scientific innovations in respect of the Shtokman gas condensate field.

   Due to that the incremental commercial reserves across the Gazprom have for the first time in the past 15 years exceeded the annual gas production output throughout 2005–2007. Some technology elements are already in use at the facilities located in the Gulf of Ob, and they will also be used at more offshore fields in the next few years.

   The main features and stages of reserves preparation. Prepared commercial reserves are the fields (reservoirs) or parts of fields (reservoirs) with oil and gas, whose structure contains at least 80 percent of category С1 recoverable raw hydrocarbon reserves and up to 20 percent of category С2.
Available classification of resources and reserves is tightly linked to the staging character of exploration works, which previously took place in the planned economy, when the state itself was the sole investor and user of subsoil assets.
In modern times, the companies-license holders can quite independently pursue their own policies of exploration work and at their own risk perform exploratory drilling, skipping some stages at once, with the traditional sequence not likely to not be observed. Various work types need to be streamlined to attain the end result with the minimum expense.

   The nature is more sophisticated and diverse than any of our conceptions about it. That fully can be referred to the subsoil assets containing minerals. Any attempt of ours to “make the reality fit” to any typical schemes is in essence the most simplified model of object and the process of its study.
However, creation of such sample action algorithms is practically the only way in perception in general and in geological prospecting in particular. The study methods and content to a great extent depend on the complexity of the subject of interest. We confined ourselves to three types of object complications based on the seismo-geological conditions:
– Simple seismo-geological conditions (Type 1).
– Complicated seismo-geological conditions (Type 2).
– Very complicated seismo-geological conditions (Type 3).

A list of applicable characteristics was developed for every one of those types. Obviously, there is a large quantity of interim objects found between these types, and also large diversity inside isolated three groups. However, they were assumed as basis in creation of the reserves preparation technology. Depending on the objects appurtenance to the groups, various modifications of reserves preparation technology (Fig. 1) can be used.

   Brief characteristics of methods used for the forecast of properties in the crosshole space. Porosity or reservoir saturation only known for the borehole points within a certain depth interval is a direct parameter describing the object. While indirect parameters will include some numeric arguments which characterize the seismic waves reflected from the depth boundaries (amplitude, frequency, energy etc.).

   Generally, the main task is to find the links available between the direct and indirect parameters at the borehole points and propagation of those links towards all seismic data in the object of interest. Otherwise, this process may be called a translation of seismic data into environment parameters.

   This  can be  schematically seen in Fig.  2.   Mathematically, the problem is incorrect. Quite a few researchers had invested a lot of their time and effort into making this problem conditionally correct, i.e. correct in the event that specific conditions be imposed on the environment model and parameters.
Oftentimes, some very beautiful mathematical solutions were obtained at that, but the calculated environment model can be quite far from the reality due to overlapping of those conditions.

   The technology emphasizes VNIIGAZ-developed various multiple analysis algorithms based for the most part on the multi-dimensional representation of the source data and the search of regression dependences.
Building a digital 3-D network model. This stage can be illustrated using the example of Shtokman GCF. For the first time, the 3-D field model was built by VNIIGAZ in 2000–2002 during preparation of a development project. Ever since, it has carried out the 3D seismic survey that served as basis for building of the new model.  

   Thus, in particular, original “glow” of gas reservoir in the field of seismic attributes can be observed in the U0 (Ю0) productive strata (Fig. 3). It eliminates any doubts in the field productivity for the patch with the С2 category reserves located in the western part.

   The initial stage of modeling involves creation of the model spatial skeleton shaping the form and dimensions of the cells in plan. The three-dimensional model body can be built once the comprehensible geometry of the framing network cells and the model boundary have been set.

   The setting of trends and directions of fault lines can be used for fine-tuning of the cells geometrics. The process of the structural model buildup is finalized with the 3D grid containing the three-dimensional cells which are further filled up by various property values. The final 3D-grid of the Shtokman field geologic model contains about 15 million of cells distributed across seven main zones.
Following parameters were determined for each model cell: porosity, gas saturation, shaliness, net sand, permeability coefficient and water saturation coefficient. Some sectional views of the geologic model are clearly reflecting all basic features of the Shtokman field productive strata composition.
The built model has been carefully studied and analysed. The obtained results allowed researchers to become convinced of correctness of the selected options of input, data smoothing, and algorithms of the crosshole correlation and interpolation considering the seismic data.

   Conclusions. Based on the completed development, it was practically for the first time that the State Reserves Committee – Russia’s superior expert body on reserves – had approved some economic reserves just on the basis of seven exploratory wells (over 500 bcm per one well).

   In this regard, the scope of reserves came to be approved in the authors’ variant without any corrections made, which very seldom occurrs in the SRC practice. All this testifies to the correctness of obtained decisions and correctness of executed building and calculations.

   Economic benefit of technology implementation just at the Shtokman GCF amounted to about $900 million. As a result of development and technology application, this value will be substantially overpassed within the next few years at more of Gazprom’s facilities.

   Therefore, all above-stated is evidence of exceptional importance of conducted studies. The preparation technology development and implementation is the major achievement not only for Gazprom, but also for the entire Russian fuel and energy complex on the whole.

   The developments were distinguished by Resolution No. 121 dated February 27, 2008 issued by the Government of the Russian Federation to give the 2007 RF Government Award in the field of science, engineering with award of the rank “Winner of the Award of the Government of the Russian Federation in the field of Science and Engineering” to the following employees of VNIIGAZ and Gazprom: Prof. Y. Ampilov, PhD (Physics and Mathematics), Research Director; Prof. D. Mirzoyev, PhD (Technics); A. Timonin, S. Sharov, Y. Stein, candidates of geology and mineralogy, employees of VNIIGAZ; V. Vovk, Candidate of Science (Technics); V. Golubev, Candidate of Science (Economics), A. Kruglov, PhD (Economy); R. Kurilkin and V. Rabkin of Gazprom.

Share it!
Copyright © 2008 Eurasia Press, Inc. (USA). All rights reserved.
Web programming by Iflexion
Copyright © 2008 Eurasia Press (